ICTIS 2013: Improving Multimodal Transportation Systems-Information, Safety, and Integration

This paper introduces the Model-View-Controller (MVC) pattern, Factory Method Pattern (FMP), and Strategy Pattern (SP) into hybrid traffic simulation modeling based on Multi-Resolution Modeling (MRM). It designs the framework of the Traffic Multi-Resolution Simulation System (TMRSS) using MRM theory and develops the architecture of TMRSS based on the MVC pattern. In addition, it founds the data structure models of TMRSS, which include route, segment, and event structures. They are implemented by the FMP and SP, respectively. Furthermore, the paper presents three patterns to implement structures of data and logic, which include framework design, architecture design, and data structure design in TMRSS. Finally, a case is exemplified to prove that the architecture and structures are available, suitable, and scalable in TMRSS.

A vehicle can be represented as an autonomous simulated agent which can be efficiently analyzed (for the vehicular behaviors and the dynamic performance of traffic flow) by using a multi-agent system. In this article, a new microscopic vehicular behavior mechanism is proposed based on a multi-agent in a vehicular sensor network (VSN) circumstance. Different from the traditional vehicle-following principles, the vehicle agent considers the behavioral decision influence by interactive communication of the signalized intersection-vehicle and vehicle-vehicle (ad hoc). The underlying idea is to establish a single-lane traffic simulation model on the basis of the influence of the VSN. According to the proposed approach, the decision of the acceleration or deceleration rate by the vehicle agent will be altered depending on the front signal phase. In this occasion, the simulations respectively verify the model on microscopic level and macroscopic level in order to analyze the time-space distribution characteristics of the vehicles by interactive information influence. The results show that the proposed mechanism and model can provide better performance than the classic vehicle following model in traditional circumstances.

The Cooperative Vehicle Infrastructure System (CVIS) can provide individual vehicles' real-time status, such as position and speed, which could serve as valuable inputs for traffic signal control systems. This paper presents a signal control method for single intersection based on CVIS. The phase-based optimization strategy procedure and models for green signal time in the rolling forecast time horizon were presented and guidance speed optimization is also described. Simulation experiments indicate that the proposed method is better than induced control method. The average delay and stops decrease are significant at both low- and high-traffic demands.

A sideslip angle estimation algorithm based on DGPS in V2I cooperative system is proposed. The vehicle kinematic model is built to estimate vehicle yaw angle and sideslip angle; meanwhile, a two-order kalman filter is used to fuse information from different sources. The first-order kalman filter is available for processing lateral acceleration, longitudinal acceleration and yaw rate collected by inertia measurement unit (IMU). This information is used as the time update of vehicle model. The second-order kalman filter is utilized to fuse vehicle location heading angles which are collected by DGPS in cooperative system. This information is used as the measurement update of vehicle model. Steady-state cornering test results show that the algorithm is effective, even if the vehicle is in high lateral acceleration. The algorithm suits vehicle safety control requirements in a V2I-cooperative system.

The technology of intelligent cooperative vehicle infrastructure helps to improve road traffic safety and efficiency. The intelligent vehicle platform is the key equipment for research and validation of the technology of intelligent cooperative vehicle infrastructure. First, the general requirements of the intelligent vehicle platform, as well as the platform vehicle motion and the way of gaining status information based on external sensors, are introduced with a focus on the signal filtering and calibration of vehicle sensors. The intelligent vehicle platform established is demonstrated to gain status information of vehicle motion accurately through a comparison test and becomes the key device for the intelligent cooperative vehicle infrastructure research.

Recently, much effort has been devoted to advancing Connected Vehicle technology. It is foreseeable that vehicles operating in networks will come to characterize our everyday life in the near future. Nevertheless, it is not yet practical to conduct large-scale experiments in the field for researching Inter-Vehicle Communication (IVC) protocols and their effects on traffic. For this reason, IVC simulation is in high demand as a means for evaluating the performance and applicability of existing network protocols and their impact on traffic. To simulate both vehicular driving behavior and networking protocols with precision, a state-of-the-art simulator must be developed that is capable of both fine-grained traffic microscopic simulation and network simulation. We, therefore, developed a High-Level Architecture (HLA) simulator called SimIVC (Simulator for Inter-Vehicle Communication), composed of a traffic simulator, PTV VISSIM, and a network simulator, OMNeT++. A study was conducted to show the effectiveness of SimIVC. In the study, two network protocols (DSRC and Wi-Fi) were evaluated in a well-calibrated road simulation network developed using the HLA SimIVC.

With the rapid development of intelligent transportation systems, it is hard for conventional testing methods to meet the testing requirements of the complex cooperative vehicle infrastructure system (CVIS). Based on analyzing various functions of the vehicle infrastructure interactive traffic safety system - the vehicle-vehicle interactive collaborative control system and the traffic coordination control system - under the cooperative vehicle infrastructure environment, it is synthetically considered the implementing scenes and venues of vehicle infrastructure system. Combining with advanced wireless communication, data exchange technology and sensor detection technology, presented an integrated testing scheme on the basis of real testing conditions of CVIS under two scenarios (i.e., a segment and an intersection). Through the on-road experiment, the integration and simplification of the scenes and venues have been achieved and the redundancy of the test system has been reduced. The experiment results indicate that the testing scheme is of general and feasible.

Cooperative vehicle-infrastructure technologies have made it possible for vehicles to collect and exchange real-time traffic information for the purpose of traffic guidance. However, traffic congestion detection using Vehicular Ad-hoc NETworks (VANETs) is inaccurate on urban expressways due to the complex road and traffic conditions. What's more, the necessary control mechanism is lacking for the dissemination of congestion information. This study proposes an urban expressway congestion detection and notification method using VANETs. The method adopts the simplified Doppler frequency shift method to estimate and distinguish the degree of congestion along major and auxiliary roads. Human cognitive abilities are used to cooperatively amend the estimation and describe the overall situation of the congestion. The method also develops a spatial-temporal effectiveness model based on the field and potential energy theory to control the dissemination range and survival time of the congestion information, thus alleviating the vehicular network congestion. The proposed method ensures the accuracy and effectiveness of the congestion information and provides a reference for driver decision making and path planning.

Transportation cyber physical systems (T-CPS) refers to the concept that cyber physical systems (CPS) is introduced into transportation systems, which can make transportation systems achieve full coordination and optimization via the increased interaction and feedback between the transportation cyber system and transportation physical system. Considering the characteristics of widespread interconnection, intercommunication, and interoperability in T-CPS, the present paper proposes a vehicle cooperative control framework based on the coordination between individual vehicles as well as between vehicles and the roadside infrastructure. Consequently, the vehicles' efficiency can be improved under the proposed vehicle cooperative framework.

First, from the point of view of road marking, this article has analyzed the visual navigation constraints which are dependent on the road geometry and the response capability of the driver. The driver's psychology has the greatest impact on the induced perception of the road in the face of the capability of the rapid response to the system of road-induced. Magnetic induction technology is cooperative vehicle infrastructure (CVI), used to track and analyze the lane, keeping cornering control and the development process of lane changing control. The Magnetic Markers induction it analyzed the application of the United States, Japan, China and other countries. Furthermore, it elaborates the new technology of the magnetization of the magnetic asphalt pavement, brings forth a magnetic induction technology of the triaxial different track isomorphic, analyzes the means of magnetic sensor technology, and discusses the comprehensive advantages and road development impact of the magnetic pavement. Finally, it describes the trend of magnetic road development.

In order to identify traffic signals in bad weather, a method of intersection signal phase formulation and transmission is developed. The total data packet of intersection information and phase information is divided into three parts (including the header files, the intersection information, and the signal control program parameter) on the basis of the intersection signal control protocol which is described separately. Taking a common crossroad as an example, the encoding rules on signal control program are elaborated by which the intersection is described and message protocol is set up. The receiving terminal in the vehicle receives the control timing of the signal lamp in the intersection through wireless transmission technology. Drivers can get the control timing of the signal lamp in the intersection accurately and previously and distinguish their driving behavior combined with the location of themselves by this method, which ensures safe driving.

Vehicular ad hoc networks (VANETs) is an emerging new communication technology which has great potential to enhance the safety and comfort of drivers. Security and privacy issues are crucial limits to the adaption of VANETs. In this article, a road-side unit (RSU)-based, privacy-preserving, message-forwarding framework in VANETs is presented. It utilizes the deployment of RSUs to deliver messages to their destinations while preserving communicating parties' privacy. It takes advantage of the high performance capability of RSUs to store and forward messages to their destinations, where these RSUs utilize re-encryption techniques to form a mixed network to provide adequate privacy for senders and receivers. The security analysis results show that the proposed framework can achieve efficient data delivery for many delay-tolerant applications in VANETs.

Cooperative Vehicle Infrastructure System (CVIS) is a complex system for interactions among human, vehicles and roads. However, there is no effective assessment methodology for intelligent tests and assessment of the system. In this paper, it has first selected the hierarchical cooperative vehicle assessment criteria based on fuzzy Analytic Hierarchy Process (AHP). Second, it has assigned weights of various assessment criteria using AHP, followed by the consistency check for the weight results of these criteria. Lastly, the CVIS is evaluated based on Fuzzy Synthesis for building the assessment system of CVIS. It establishes a theoretical foundation for CVIS testing and verification.

Cooperative Vehicle Infrastructure System (CVIS) - which applies advanced communication technology, automatic control technology and computer technology to realize the interactions among human, vehicles and roads - is a complex system to improve transportation safety and efficiency. The system validity and reliability is the key to make this system practical. Presently, however, there does not exist a comprehensive and effective test standard and environment to verify the system. In this paper, starting with the typical application demands of CVIS in intersections, it has built a framework of traffic scenes for the verification of CVIS under the intersection environment, through the extraction of static traffic elements such as the natural environment, intersection channelization, etc., as well as dynamic traffic elements such as various conflicts of pedestrian - vehicle, vehicle-vehicle, vehicle-traffic lights, etc. Moreover, it has designed some typical application scenes in intersections to instantiate the framework. Results of this paper can provide some guidance for the integrated verification of CVIS, and establish a practical foundation for the test and verification of typical CVIS applications under intersection environments as well.

The research of traffic mode choice behavior is the basis of traffic demand forecasting. By studying the resident's travel mode choice behavior, paper constructing the structure equation model to formulate the traffic demand management policy of the residents travel requirements based on this optimization of urban traffic structure and establishes the health of the transportation development mode from the perspective of behaviorism. The travel mode choice behavior of the urban resident is explored at the community scale. An example of Beijing is discussed and 349 samples from three communities are provided. Moreover, an interaction between the internal and external attribute and the travel behaviors of residents are presented which use the SEM. Among all of the variables, the internal and external attribute is the fundamental variables, while the travel purpose is the key variable. Resident's traffic mode choice behavior can be summarized as "internal and external attribute decided to travel purpose, travel purpose influences the travel time and travel mode". Through the quantitative analysis of interaction relations between departure time choice and travel time, the influence of residents various attributes to walk, bicycles, buses and cars can be obtained.

The more traditional approach for driving behavior recognition is based on video signal processing techniques, with the disadvantages of undesirable modifications to the vehicle (e.g. mounting a video camera oriented toward drivers) and a large amount of data processing. In this paper, a new approach is proposed using mobile phone sensors as detection devices to identify the behaviors and status of drivers. Our proposed method can detect several basic driving behaviors: starting or stopping, braking or acceleration, and turning right or left. The experimental results have justified the feasibility of the method.

Timely and accurate identification of the driver's intention is considered helpful to avoid collisions. Driving in an on-road traffic situation makes it much more difficult to recognize the driving intention because of dynamic and uncertain information. However, the intentions can be inferred by the driver's behaviors as he prepares to execute an action. The current studies focus on classifying driving intentions into car-following and lane-changing. Therefore, a lane change intention recognition method was proposed in this study. A total of 10 on-road experiments on freeways were conducted to acquire time headway, driver's eye-motion data, steering angle and lane departure data. With these data, the typical features under free driving and lane change conditions were analyzed, respectively. The Back-Propagation Neural Networks method was applied in this study to achieve the driving intention classification function. The proposed model successfully recognized 95 intentions in 100 lane change behaviors. The recognition result of the model can fit the target output at a degree of 0.99. This model is useful for surrounding drivers to choose the safest route to avoid collisions in the vehicle-infrastructure technology.

In the United States, Britain, France, Russia, China, and other countries, much of the road-crossing traffic occurring has traffic congestion problems. During a storm, earthquake, war, or other special circumstances, some cross-sections are completely cut off and cannot be recovered timely. In order to avoid such situations, we need to destroy the old transportation scheme and establish new ones. Redesign the transportation scheme using the "push stone" method to cancel the traffic light, dismantle the overpass, convert the stereo traffic for plane transportation, and realize zero traffic congestion. Establishing a push stone traffic model consists of seven parts: polymerization area, bifurcation area, back area, straight area, surround area, off area and service area. These parts all solve congestion problem that is caused by cross traffic in the world.

The data of mountain rural roads, including traffic compositions, operational speeds, number of crashes, and road horizontal alignments, were collected and the impact test conditions of safety barriers were determined. The vehicle type which requires special protection and its actual mass status were considered in the selection of the test vehicle type. Using the method of statistical analysis, the operational speed of the corresponding vehicle type was selected as the impact speed. Based on the analysis of crash cases and road horizontal alignment, the impact angle was confirmed. With a comprehensive consideration of China's current economic conditions, the goal of crash prevention, and the system construction of the performance classes, it was determined that the safety barrier's containment energy is 70KJ and the performance class is B on the mountain rural road. The corresponding impact test conditions are 19-seat minibuses weighing 6t with an operational speed of 42km/h and an impact angle of 25 degrees.

Based on a regression analysis of field test data obtained from provincial Highway 203, the correlations of speed standard deviation and traffic conflicts along two-lane highways were determined in this paper. The relations of speed standard deviation, strength of traffic conflicts, and traffic accident rate are analyzed, and their internal relations are established theoretically. The results show that there is a remarkable correlation between speed standard deviation and strength of traffic conflicts on two-lane highways. Among the diversified regression models used, the correlation coefficient of the polynomial regression model is the highest.

The expressway has played a great role in promoting the development of the national economy in China; but, because of its characteristics (which include high speed, closed off, and great traffic flow), unexpected incidents are more detrimental than along ordinary roads. The purpose of this paper is to provide scientific and technical support for incident decision-making methods on expressways. With the methods of data reporting, data collection, data input, data analysis, incident management, and leader decision, the effective operation of the inquiry and analysis mechanism is the focus of this paper. Based on Intelligent Transportation Systems, expressway emergency processing systems use new technology and ways to: handle the accident quickly, accurately locate and identify dynamic rapid rescue lines, and solve the issue with new ideas. Three layers of calculation structures are established involving a standard web server, an application server, and a database server. Also, the distributed objected-oriented design method, TCP/IP safety protocol, and java web service techniques are applied. Based on geophysical and geographical data, warning databases, crisis databases, prediction and evaluation models, emergency command databases, and expert knowledge, the databases are finally established.

Expressway guide sign is important for traffic safety. The selection of control information of expressway guide sign has a strong impact on the effectiveness of expressway guide sign. Most of the previous studies on the evaluation of control information of expressway guide sign are aimed at qualitative analysis or quantitative analysis without considering the data of operating period, especially the network toll collection data. So some systematic investigation and analysis work are completed using the network toll collection data collected from Guangxi Zhuang Autonomous Region in China. The useful data are abstracted and the calculation method of cross-sectional traffic volume is provided. Based on these analyses, the concept of traffic gravitation is proposed and model of traffic gravitation between two cities is built which considers the factor of distance, the factor of cross-sectional traffic volume, and the factor of regional differences in China. The value of traffic gravitation can be calculated by the model of traffic gravitation. By comparison of the value of traffic gravitation among different control information, the control information whose traffic gravitation value is largest can be selected as the right control information. In this way, the present control information can also be evaluated. The flow chart of evaluation of control information of expressway guide sign is also provided. This quantitative evaluation method has already been used for road safety evaluation in Guangxi Zhuang Autonomous Region in China.

In order to effectively attack motor vehicle speeding violations on freeway network and to prevent road accidents, the paper describes the current situation and problems of freeway traffic safety control in China, puts forward solutions for monitoring and controlling motor vehicle running-speed on freeways. By integrating the technologies of motor vehicle monitoring, license plate recognition, mass information transmission, communication, and distributed computing, a vehicle's point-to-point speed on its whole travel section can be obtained. Then, we can promptly notify the speeding drivers in the right time and place, or even give tickets to those drivers at toll stations. We can also periodically evaluate the traffic safety situations on the freeways. The monitoring and controlling software was developed and implemented. The demonstration project in Jiangsu Province proved that the system functioned effectively, and enhanced the dynamic enforcement capacity of traffic police departments. This paper describes the overall architecture and the main features of the software system. It also discusses the key technologies and solutions.

Both electrical properties and piezoresistive behavior of the cement-based composites containing copper-coated steel fiber (0.5 vol. %) and graphite powder (0~25 % by mass of the binder) were investigated. This type of material can be used as sensors to be embedded into pavement for traffic-weighing or into bridges for strain-sensing. The change in resistivity of this material with stress under cyclic uniaxial loading was tested. No matter what the content of the graphite powder that was added in the composite, the corresponding relationship between stress and resistance variation can be observed. The results showed that when the content of graphite powder was 15%, the sensitivity to stress was higher relative to the others contents of graphite powder while its resistivity electrically was 1474.874 Ω⋅cm, and the compressive strength was 40.3MPa at 28 days.

Road work on urban expressways in a certain time period usually reduces road capacity, worsens traffic safety and, therefore, results in relevant traffic operational risks and traffic safety risks. At present, in the situation of more frequent road workings, it is important, in terms of improving traffic safety management of urban expressway road work, to study the risk evaluation methods of road work zones on urban expressways systematically, and to evaluate the traffic safety risks and traffic operational risks of road work zones on urban expressways precisely. In this paper, the traffic safety risk and traffic operational risk of road work zones on urban expressways were explored and, based on consistency analysis of operating speed and traffic performance analysis, the risk evaluation methods of road work zones on urban expressways were established. On the basis of application on risk evaluation of road work zones on Beijing expressway, the effectiveness of risk evaluation methods of road work zones was verified, and improving measures on reducing traffic safety risks and traffic operational risks were presented.

Hi-Pass was introduced at the meeting of the Ministry of Land, Transport and Maritime Affairs and was first opened in June 2005. Since the utility rate of Hi-Pass in 2011 was 50.7%, it has been increasing by nearly 10% annually. With the increase in the use of Hi-Pass, however, there are growing safety problems. At this point of time, a criterion on Hi-Pass lane arrangement is required. Thus, this research suggests a three-stage highway lane arrangement method of mainline toll booths. This study is mainly based on conflict analyses and a conflict model is established.

The interactions among closely located piles are complex in super-long pile groups. Few data are available on the testing of full-scale bored pile groups in the field. To investigate the behavior of super-long bored pile groups, axial static load testing of in-situ and full-scale instrumented pile groups and single piles were performed. An alternative to modeling pile interaction and calculating individual pile response is to model the pile group as a single foundation unit in what is referred to as the equivalent pier method. Based on nonlinear pile-soil-pile interaction modeled by hyperbolic load-transfer functions and the group effect of reduction of stiffness and increase of head settlement, it was found that the initial stiffness reduction coefficient β of 0.3 is suitable while the value of g ranges from 0.15 - 0.4 for this field tested pile group.

In this paper, a novel simulator is designed and implemented to run the simulation for large-scale crowds in real time in a city-wide map, which can provide useful insights for the relevant authorities in time. In detail, in this simulator, each individual in the large-scale crowd is denoted as an agent, and each agent's behavior must obey the fundamental physical principles. Since the behavior of each agent in the large-scale crowd should be computed, it requires large computing resources. This simulator utilizes CUDA (a GPUs parallel architecture) to improve the performance. In doing so, the simulation with thousands of agents over a city-wide map can be run in real time by using a single PC or laptop equipped with NVIDIA graphics card. Based on the designed simulator, simulations were conducted to show how to draw useful insights from the simulation.

Many accidents occur at intersections where conflicts between right-turn vehicles and pedestrians are most common. The "right turn on red" (RTOR) control scheme is widely used in China. Recently, protected/permissive right-turn phasing (PPRT) control scheme has been adopted in some cities. However, little research has focused on the effects of reducing conflict numbers or decreasing conflict severity under PPRT. This paper presents a comparative study of the behavior and conflict characteristics of right-turn vehicles and pedestrians under different right-turn control schemes. Empirical data has been collected at two typical intersections with similar layout characteristics and traffic patterns, one with control scheme of RTOR, and the other PPRT. The conflict samples are classified into 10 types, according to the direction of pedestrians' movements and whether pedestrians cross individually or in successive groups. Time-lags and gaps of right-turn vehicles and pedestrians are extracted. The analysis results show that time-lags and gaps significantly correlate to the yielding behavior of right-turn vehicles. Furthermore, the time-lags and gaps with RTOR are smaller than those with PPRT, which indicates that the conflicts with RTOR are more serious than those with PPRT. Meanwhile, right-turn vehicles are more likely to yield to pedestrians at PPRT intersections.

JTJ074-94 was published in 1994 and revised in 2006. The biggest difference between before and after is the requirement of crash performance. In JTJ074-94, the anti-collision grade is B, and the anti-collision energy is 70kJ. In JTG/T D81-2006, the anti-collision grade is A, and the anti-collision energy is 160kJ. Because of the upgrade of the requirement of crash performance, the important question is to improve the protection capability of the guardrail in highway reorganization and expansion. However, the double w-beam barrier is the most domestic and applicable in many transformation methods, but the crash performance has not been proved. The protection ability of double corrugated beam barriers has been verified by simulation experiment. This simulation experiments also lay a foundation for the real vehicle crash test.

The navigation environment is the foundation of shipping, and it is also the key influence factor in shipping safety. This paper takes the Changjiang River as an example, and through the statistics of its shipping accidents and dangerous case data, explores the contribution of navigation environment elements to accidents based on the Bayesian network. Finally, a navigation environment safety index system is established which can dynamically represent the navigation environment safety state trend with the exponential form as its continuity. The release and forecast of the navigation environment safety index is beneficial for enterprises, government departments, and industry authorities related to shipping to take charge of the navigation environment security situation and trend. It also has an important practical significance to improve the Changjiang River navigation safety management level.

A new disaster survey method along the highway was explored by combining multiple high-resolution remote sensing data, geological materials and other basic data. By analyzing the geologic environment and its history disasters along the highway, remote sensing monitoring index, assessment methods, mathematical models are constructed and studied to evaluate the dynamic risk of geological disaster on highway disaster prevention, road planning and highway security guarantee.

Based on the domestic and international secure and emergent transportation platform status quo, the paper analyzes its bottleneck problems such as the low rate utilization on basic resource, the incompletion of traffic monitoring information, the imperfectness of early-warning mechanism and the inconsistence of emergency response. By taking advantage of the new technology of multi-source information fusion technology, the cloud computing, the internet of things (IOT), and Mobile Internet, this paper proposes the solution for the secure and emergent transportation platform from the early-warning of monitoring, the integration of a variety of information to the cooperation of emergency response among multi sectors. The paper further discusses the construction thoughts and the potential application for the future transport emergency platform.

Implementing traffic safety evaluation is an efficient way to improve road safety, especially for newly designed roadways. In this paper, a new method of road safety evaluation, based on the vehicle driving simulator, was studied. In this study, a large number of experiments are implemented. Combined with the data of vehicle speed and vehicle lateral offset collected from the driving simulator during the process of simulation, drivers' psychological and physiological data are collected and analyzed. Unsafe road sections and the main factors were studied from the statistical data. The data analysis results indicated that typical data can express traffic safety risk. The research results could advise the alignment design and ancillary equipment design for newly designed roads and improve traffic safety in advance.

This paper first explores reasons and risks of run-off-road crashes, then introduces a lane departure warning system (LDWS) in the hope of reducing frequency of such crashes substantially. Deviations were divided into three levels. In this research, Badaling Freeway was selected as the study roadway section. According to historical safety records, traffic crashes occurred frequently on this freeway heading to Beijing direction, which was located in mountain areas. Paper picked out segments between 51.5 km and 55.6km to collect pertinent information of drivers' lane departures by digit video for a week. Lane departures data were detracted by digit video from 10:00 am to 16:00 pm for one week. Observed departure values were divided into several groups and aggregated into four categories to orient different levels of vehicles leaving behaviors. Result lays a solid foundation for further development of lane departure warning system (LDWS) for mountainous freeways in China.

This paper introduces the development process of the Automated Guided Vehicle System, which is China's independently-developed intelligent container transport vehicle system. The system consists of positioning and navigation systems, wireless communication systems, automated guided vehicle systems, and intelligent control systems. In the development process, such key technologies have been tackled as automated guided vehicle system integrated technology, automated guided vehicle path planning and tracking technology, positioning navigation and precise positioning technology, and intelligent operation decision-making system. Currently, the system has been put into trial operation; the main technical parameters have reached the international advanced level. The paper ends with the applied prospects of the system in China's container terminal.

The lane change movement on a highway is a demanding and critical maneuver as it involves the surveillance of vehicles both in the original and targeted lane as well as the control of both longitudinal and lateral movement. However, intelligent vehicles make it possible to develop precise control approaches to safely achieve lane changes. A Model Predictive Control (MPC) system for safe lane changes with a path-tracking capability is proposed in this paper. First, a safe lane change trajectory is planned with consideration of collision avoidance and comfort using a polynomial path planning method. Then, a nonlinear vehicle lateral movement model is constructed and validated using the fully nonlinear vehicle dynamics simulation software CarSim. After the established vehicle model is successively linearized, the linearization result is employed as the prediction model of the MPC controller. Based on this, the safe lane change MPC controller is designed. Simulation results illustrate the potential of the controller when following the safe lane change trajectory.

In order to extract the lane lines accurately, this paper proposes a Limited-area Hough Transform (LHT) based on the region of interest (ROI). This article first preprocesses the color image, finds the vanishing point, and gets the ROI through an improved translation according to the vanishing point. Finally, two lane lines are extracted accurately by the LHT. Simulation results demonstrate LHT has higher real-time performance and a quite high recognition rate compared with the standard Hough Transform (SHT).

A lot of researches ignore authenticity and integrity check of reported data from remote monitoring devices, which may result in security concerns. Considering potential attacks - such as data forgery and historical data replay - this paper puts forward a method to implement a customized encryption algorithm coupled with MCU IAP (In Application Programming) capability to enhance security, which can satisfy classified security requirements, and guarantee the data confidentiality, integrity, and freshness with rational cost. This framework makes the same device have wider application fields and comply with distinct criteria. For secret department, malicious data cheating may be dangerous if security check is ignored.

Complex operating environment sections were analyzed to determine the risks from geometric line conditions, road facilities' characteristics, traffic environment and climatic environment. Risk Warning System for complex operating environment sections of expressway was designed by five subsystems: Risk information collection and releasing module, RFID based dangerous goods vehicles monitoring module, GIS-based database management module, risk warning module, and driving safety management decision-making aiding module. Based on the safety decision-making model for measurement type and safety speed control standards, which were proposed under various pavements conditions, visibilities and traffic environments, the system is capable of supporting complex operating environment sections of express way risk control, traffic flow coordination and emergency management, etc.

The safety problem of mass injuries and death caused by operating vehicles is one of the most difficult problems faced by the field of traffic safety in China. Using the Internet of Things technology, the system of key operating vehicles inter-connection and inter-surveillance was built through car GPS system conveying vehicle dynamic information, accessing to government and corporate monitoring platforms, and switching public data, sharing of vehicle information in cross-regional can be achieved, so that the joint supervision in cross-regional could be possible. This article analyzes the system of Internet of Things' basic framework, operating mechanism, and existing problems during its operation, and proposes the improved measures for increasing the on-line rate of operating vehicle to grid and achieving reasonable docking in different platforms.

The speed distribution of each main component of freeway work zones was investigated and analyzed in this study. The following four kinds of freeway work zones were investigated: the closed one-way running lane work zone, the closed one-way passing lane work zone, the closed one-way lane work zone, and the closed one-way transition region work zone. The average speed (i.e. the 85th percent speed), the speed difference, the speed difference between small and large vehicles, and the high-speed vehicles' percentage were then determined for each component. Furthermore, statistical results concluded that moving downstream from the upstream normal area, the warning area (or transition area), and finally through the activity area of work zones, the standard deviation of the speed distribution, as well as the speed difference between small and large vehicles, noticeably decreases. According to the law of vehicle speed distribution, speed control principles, and suggested limited speed values were proposed for each component of freeway work zones based on the characteristic of the speed statistical distributions.

In recent years, "internet of things" technology has become of increased interest. According to "internet of things" application demonstration project of maintaining road traffic unblocked in extreme meteorological conditions", the first batch project of Internet of things in Beijing, this article introduces the application of internet of things technology in road traffic weather. Through real-time monitoring and analysis of meteorological information, this article constructs the system of road traffic meteorological service. The system can forecast and an early warning of the ponding depth, visibility, surface temperature, snow depth, ice and other situation of traffic trunk, improve the level of road traffic management, ensure road traffic safety and smooth in extreme weather conditions.

Frequent inclement weather seriously impacts a traffic system, and maintaining smooth traffic in bad weather is an important problem to city and highway traffic. This paper is based on the "internet of things application demonstration project of maintaining road traffic unblocked in extreme meteorological conditions". The first batch project of the internet of things in Beijing proposed the basic location of maintaining road traffic unblocked in bad meteorological conditions; using the top design theory and method of traffic information system with the core of service function, analysing comprehensively the function of system service, raising the overall system architecture, analyzing three-level architecture of maintaining smooth traffic in bad weather of the city/key management departments/emergency support teams, and the mechanism of system operation, data sharing. The beneficial discussion on the total system framework and operating mechanism of maintaining traffic smooth in bad weather is valuable to the standardization, extendibility, and the sustainability of system construction.

In the process of Chinese domestic car-transporting largely exists some problems, which involve over-speed, driving when tired, cross-district driving, leakage and stealing of gasoline, transport damage, false declaration on road toll, fuel bill and maintenance cost. In order to avoid potential safety risks and get an optimized route of car transporter, this research aims at resolving these issues on monitoring and locating car-carrier and commodity cars. This paper develops a framework integrating IoT and mobile platform for transportation process monitoring of car-carrier. Based on this research, a mode of process monitoring of car-carrier in IoT environment is proposed, which is beneficial to effectively reducing logistics cost and improving the utility of the logistics management.

This paper aims at presenting the research work regarding the formalization of dependability-related localization attributes within the framework of the European project QualiSaR. The processing of natural language is used with the aim of creating a structure of dependability and safety-related terms for evaluating automated systems in general and satellite positioning performances more specifically. The attribute hierarchy developed is managed by the help of Igloo, a Natural Language Processing (Nlp) tool. The standardization objective of this research work consists of making a proposal for an international standard, which describes satellite-based system quality criteria that is understandable by transportation communities.

The violating traffic rules adventure will be taken when the non-motor driven traffic unit has waited so long that it exceeded the red light bearing. At this time, the intersection direction in motor vehicles at the end of the green light are eager to cross the intersection and accelerate in the green light time and, accompanied by the line of sight keep out, are now vulnerable to serious traffic accidents. At night, when most of the intersection signal control is the yellow light flashing, the vehicle speed is high, and a non-motor traffic unit has a greater risk to cross the street. In view of the above type analysis braking process, this study constructs the collision model of the intersection between non-motor driven traffic units and motor vehicles and designs a collision warning algorithm process and early warning system. Finally, an intersection test system was conducted in Changchun; the experiment results show that the system has strong reliability.

In order to enhance the application value of the transportation data center further, it was essential to use business intelligence (BI) technology for data mining, analyzing, and displaying. On the basis of summarizing the status and trend of BI technology for data display and analysis, the general methods of the analysis process for the data center were summarized. Taking the taxi meter data of Beijing as an example, the structure of the original data was analyzed and the calculation method for the taxi operation index was put forward. The indexes were put forward, including operation mileage, operation time, number of carrying passengers, income, and so on. They were analyzed from different dimensions using BI technology. The functions of historical data query, report output, and others were provided, supporting the taxi operation management and decision.

Currently, the world is suffering from daily recurrent traffic congestion. Traffic engineers have developed the ATDM control system as a countermeasure to mitigate the problem of traffic congestion using various active control measures. In 2011, the City of Edmonton initiated a study to develop an integrated active traffic control system targeted at improving the efficiency of traffic operations on a major freeway corridor around Edmonton. The Dynamic Traffic Analysis and Management (DynaTAM) control system has been designed to implement the integrated control through Ramp Metering (RM) and Variable Speed Limit (VSL). DynaTAM is a Model Predictive Control (MPC)-based, pro-active traffic control system. In this paper, the control framework of DynaTAM is presented in brief.

With the development of economy, the quantity of the motor vehicles in China has had a rapid growth. The vehicle's intelligence level is also on a rise as more and more ITS technologies have been applied in more and more vehicles. This paper analyzes the advantages of ITS on improving road safety, proposes a classification about the in-vehicle ITS technologies which could improve road safety, concludes the status quo and prospects for application of the in-vehicle ITS technologies on road safety in China and, finally, discusses the potential influencing factors in their large-scale application in China.

In this paper, a VISSIM model is set up for a highway-railway corridor with three highway-rail grade crossings (HRGCs) located near signalized intersections on a major arterial roadway. The signal controller, with preemption functions, was coded using Vehicle Actuated Programming (VAP) language (PTV, 2010), which is an add-on module of VISSIM. The VAP controller can emulate the preemption functions for multiple trains in both the signal controller and the train signal controller from the field. The traffic conditions and the train traffic characteristics in the model were calibrated to local field conditions, using empirical train and traffic data. Finally, the characteristics of the non-steady state traffic conditions, due to westbound and eastbound trains passing through the corridor, were evaluated using the model.

This paper outlines the fundamental principles of traffic flow modeling and proposes the computer simulation implementation methods of three modules: vehicle generation, speed discrete distribution, and vehicle motion. Based on that, a microscopic simulation approach of freeway traffic flow based on cellular automata and the relevant technical process are established and then tested in the typical sections of Xihai Freeway in Jiangxi Province of China. According to the results, the traffic flow simulation technique based on cellular automata can precisely represent the complicated dynamic performances of a freeway system, and this technique provides a new efficient approach to the microscopic simulation of freeway traffic flow.

This paper presents a transit signal priority (TSP) model designed to benefit both bus riders and passenger-car users. The proposed method, mainly for headway-based strategy, provides a reliable way to determine the optimal green extension duration in response to multiple priority requests from different bus routes. Also, a basic method for queue length estimation is presented to evaluate the impacts of TSP control on passenger cars. The control objective is to minimize bus passenger waiting time at the downstream bus stop, simultaneously ensuring the total person delay of entire intersection is not increased. Using the microscopic simulation, the proposed strategy has shown its benefits in reducing bus passenger waiting time and total intersection delay.

Traffic congestion has become a serious social problem. One way to ease traffic congestion is traffic volume forecasting, which is helpful to support decision-making for management or provide better route selection for passengers. Nowadays, the historical traffic flow data are used as the original input data for predictor training in forecasting and proves helpful for forecasting. However, other non-historical factors, such as weather condition and holidays, can also influence traffic volume and are often ignored in recent forecasting researches. This paper applied a Multivariate analysis of variance (MANOVA) for analyzing the relation between traffic volume and the unhistorical factors. The experiments are carried out on the data collected from a section of a national road, which show that weather conditions and holidays are helpful for traffic forecasting.

SAT Project (US 6.431.078 B2) is a three-dimensional transportation system - a dynamic transportation system - which will create the first step towards breaking up with the bi-dimensional use of modern cities. It is designed for the transportation of people and/or freight (around 15-20 passenger per unit). It consists of unitary electric-vehicles, working under different directions of movement: horizontal, vertical, and on a gradient. Its tracks are modular structures in the form of suspended tubes requiring minimum supports. Vehicles will work under various displacement directions (suspended, laid on tracks, and laterally supported). It will consequently act as a catalytic tool towards the re-definition of urban space, generating mutations on architectural morphology and typology. It is a private-public transportation system, due to the possibility of interacting under different urban scales - from smaller and private to larger and public. SAT project will provide a possible sustainable solution to the new demand and requirement for urban transportation in the future. In this paper, a first attempt for developing a library of simulation building block is discussed in order to be able to evaluate the SAT-project, its' merits for reliable logistic service, technical feasibility, environmental benefits and cost performance.

A bi-layer cooperative framework is developed to capture pedestrian behaviors at integrated passenger hubs under complex topological environments. In the framework, a simulation model is proposed based on multiple agents for pedestrians on a platform floor, in which grid agents, pedestrian agents, and the service interface are defined in detail. To precisely describe the irregular boundary of obstacles, a finer grid is used for spatial discretization of the platform floor. To conveniently and accurately describe the interaction among pedestrians in crowds, each pedestrian occupies multiple grids instead of only one, and the edges of the pedestrian can be overlapped while the core is exclusive. A pedestrian can select one of the twenty possible directions to move. The interaction rules between pedestrians themselves or between pedestrians and environments including exits and obstacles are built. Furthermore, a superimposed algorithm of the attractive field from the exit is proposed to simulate complex topological environments with multiple exits and inner obstacles. The average velocity of pedestrians and the trends of evacuation time versus the impact factor of pedestrian herd mentality and familiarity degree on exit position are discussed by simulation experiments.

In order to truly optimize the urban passenger transport station system and effectively improve the urban passenger organizational structure as well as the passenger organization performance, the constraint conditions of the layout and the site location of comprehensive passenger hubs have been proposed in the paper from the macro aspect and the micro aspect in the basis of analyzing the layout mechanism of comprehensive passenger hubs. Based on this, the dual-constrained layout and site location model of comprehensive passenger hubs have been established and the heuristic algorithm to solve this model has been also proposed. Finally, the scientific nature and the operability of this method in practical applications have been also confirmed by examples.

Different from the previous research, this paper presents a dynamic congestion pricing model based on the Stackelberg game between the government and the travel individuals. Firstly, we build a travel cost function for various travel modes from the time cost view. Different from the original literature, ride comfort of various travel modes and dynamic charge rate of government are introduced into the bottleneck model. For the government and travel individuals, Nash equilibrium is employed to describe internality and externality of traffic system respectively. Finally, numerical examples are provided to explain the relationship of these variables.

"Active Learning" in the transportation English context is chosen as the major topic in an interactive perspective, and empirical research has been conducted to investigate the relationship between individual learner differences and active learning. In this experiment, the author selects 60 first-year transportation majors from Wuhan University of Technology, thus forming an experimental group and a control group. Through a series of procedures, the author categorizes data from questionnaires, language tests and interviews. The research-based findings demonstrate that the contrast between the two groups is striking. The major conclusions obtained from the present investigation are that: (1) active learning is more effective than the traditional teaching approach and instruction; (2) there are some correlations between active learning and affective variables of the individual learner (namely, motivation and attitude); and (3) there exists no clear-cut relationship of personality variables of the individual learner to active learning, namely, field dependence/independence and extroversion/ introversion.

Many models of trip attraction based on land utilization ignore the differences among land utilization weight factors of different traffic zones. In this paper, a trip attraction prediction model, which clusters the land utilization, is studied. Considering the distinctions among the land utilizations of traffic zones, the traffic zones are classified into dissimilar groups by dynamic clustering analysis with principal component scores. Then, land utilization weight factors are calibrated by groups using regression analysis, until all types of land utilization included in different traffic zones of dissimilar groups are endowed with corresponding weight factors. The main parameter adopted here is "Importance of Traffic Zone". Finally, the trip attracting volume can be predicted. With a numerical example using the data collected in a field investigation in TongLing City, it is verified that the model has better accuracy and practicality.

Rural road networks, together with national and provincial road networks constitute a complete road network system. It is widely distributed, covering most parts of the rural areas. Road network layout is a core part of the road network planning system; its rationality and feasibility directly impact the success of road network planning. Based on the characteristics and research of rural road network layout, a method combines Fuzzy C-Means (FCM)) clustering algorithm and traffic location method. The validity of the method is tested through an application example.

The reasonable layout and planning of the expressway network is an important way to solve the urban traffic problems. The recommended value of the minimum inner-ring radius of the expressway has been provided in this paper. The layout method of the expressway based on the division of traffic units has also been improved. At the same time, according to the traffic location theory, the layout methods of the annular expressway network and the non-annular expressway network have been provided. In this paper, Harbin is taken as the example. The layout program of the expressway network in Harbin has been offered and the feasibility of the method has been provided in this paper.

The use of GPS is mainly focused on the slope deformation monitoring for highway safety monitoring, both at home and abroad; but, the research about GPS monitoring data for concealed works, such as tunnels, is little. Because of its advantages, it is a trend that GPS monitoring technique will be used for tunnel deformation monitoring. This paper uses the GPS monitoring technique to monitor the deformation of DA Shan-Po Tunnel in real time, and verifies the feasibility of the GPS monitoring technique used in the DA Shan-Po Tunnel through data processing and analyzing. We hope that the study will provide reference for similar projects.

With the rapid development of transportation construction in China, bridges with diseases became more and more abundant, and bridge reinforcement became a new topic facing bridge constructors. This paper, combined with the practices of bridge construction and maintainance, analyzes the factor of structural formation diseases of beam bridges and arch bridges (particularly, the disease causing a concrete structure taking a bad turn), and puts forward a relevant disease treatment and prevention measures to improve the overall quality and carrying capacity of the bridge structure. This extends the service life of the bridges as much as possible, ensuring the safety of bridge traffic.

It is strategically significant to make full use of the unique geographical advantages of Fujian Province and reach the idea of building cross-border cooperation areas by reaching development of cross-strait integration; that is, to construct the transportation infrastructure of the urban agglomerations on the west side of the straits between the Fuzhou metropolitan area and the Xia-Zhang-Quan metropolitan area, to shorten their spatial distance, and to form a mutual intermediation transportation network among highway, intercity fast-track, intercity rail and passenger-dedicated lines of high-speed railway between the two city groups. In this paper, we analyze the present situation of the Xia-Zhang-Quan metropolitan area and difficulties faced by the angle of its constitution and strategic position. The paper builds a traffic pattern of the Xia-Zhang-Quan metropolitan area and finally puts forward a tentative plan to achieve the vision of integration of public transport resources through qualitative and quantitative analysis.

With the development of highway traffic, the bearing capacity of many old bridges had been unable to meet the operational requirement. Many diseases had occurred. The old bridge reinforcement became an urgent problem to solve. This article mainly has studied the commonly used methods on strengthening T-beam transverse connection in the reinforcement. According to the disease that the Hekou Bridge T beam transverse connection was weak, this article put forward two ways to reinforce the connection; one is the method to reinforce the diaphragm beam, the other is to reinforce bridge pavement to form "composite beams". Analyze the stress and deflection of the two-way by the finite element; the value of the "composite beam" method is smaller, so choose the latter one to do reinforcement. Then, analyze the positive effect and negative effect of the "pavement effect"; draw the conclusion that the specific reinforcement method should avoid the negative effect, and take some construction methods to form "composite effect".

The HuaZhong Logistics Company is a big third party logistics enterprise in Wuhan; the existing vehicle scheduling model of tobacco distribution needs to be improved. This paper makes full use of existing optimization techniques to achieve optimal delivery vehicle scheduling and puts up with some measures to improve the scheduling mode.

With the rapid development of road construction, the contradiction between urgent conservation needs and limited conservation funds is becoming more and more prominent. The traditional conservation management model is gradually replaced by the development and application of pavement management system. Relying on the requirement of the road management department of Suzhou, the architecture of Network-level Decision Support System for Urban Road (NDSSUR) was constructed first. Then, a detailed analysis of the most important three parts of the system - performance evaluation, maintenance decision and performance prediction - were carried on. Finally, based on the local dynamic detection data, NDSSUR was applied to evaluate pavement performance, suggest large and medium repair, and do a long-term planning for five years within the urban areas of Suzhou. Results from the program fit the actual condition of the road well.

Language variation study is the major subject in sociolinguistic discipline. Since language is a living thing, it contacts with language varieties and changes. Language variation grows fast and diversely because of the popularization of internet and mobile phones. Since university students have a strong ability to create novel words and accept language variation, there is a survey on mobile phone short messages of university students'. The paper takes a sociolinguistic view and combines quantitative analysis to discuss three topics: (1) language features of SMS, such as brevity and shortness, having meaningful punctuation, and using numbers and symbols instead of words and so forth; (2) four types of language variation in SMS and the influence of dialect; and (3) some approaches of social factors in SMS, as well.

Proceeding from the internal coordination and the external adaptation of the channel's passenger transport structure, this paper establishes four indexes: fitness, equilibrium coefficient of comprehensive supply, transport efficiency, and sustainable development level. It then defines their value range according to the actual situation to establish a membership function of each evaluation grade corresponding to each indicator, thereby constructing a fuzzy comprehensive evaluation model for the passenger transport structure of the comprehensive channel. Further research is also conducted to study how to determine the fuzzy judgment matrix and weight. Finally, the Beijing-Shanghai channel is selected to carry out empirical research and verify the reliability and practicality of the model, which improves the analysis theory and method of the passenger transport system of the comprehensive transportation channel.

A serious competition existed between the electric bike (e-bike) and the bus on medium and short trips. In order to ensure a safe, orderly, and smooth flow of city traffic, this paper researched thee-bike travelers' intentions and boundary conditions for the transfer to public transport. The socio-economic characteristics, traveler trip characteristics, and potential trip model choices of e-bike travelers were investigated using a questionnaire. Based on the questionnaire data, the influencing factors, such as bus fares, bus travel time, management policies and care factors on the travel model choice, were analyzed to obtain the regularity of the behavior of the users. The RP model, SP model, and the RP and SP data fusion model for e-bike travel choice were established, based on Binary LogitModel. Finally, sensitivity analysis of the factors was performed. Jinan had been chosen as a case study. The results show that: (1) the parametric test veracity of the SP and RP data fusion model is satisfied; (2) people on the sensitivity of the ticket price level far outweighs the sensitivity of the degree of time, nearly 10% of the e-bike trip to the bus transfer can be achieved by reducing fares; (3) implementing management policies, reducing bus waiting time, improving the efficiency of public transport and setting free BRT transfer points can promote people to take bus instead of e-bike.

For the performance evaluation of heavy vehicle emissions and fuel consumption, based on heavy-duty chassis-dynamometer and constant volume sample (CVS) system, this paper analyzes the influence of different cycles on emissions. The NO_X, HC, CO, and CO₂ mileage emission factors and hundred kilometers fuel consumption of the China City Bus Cycle (CCBC) are 1.91 times, 36%, 1.42 times, 1.33 times, 1.27 times of China World Transient Vehicle Cycle(C-WTVC, respectively. Research the contribution of the different operating modes of the different cycles, including accelerate, decelerate, constant speed, and idle. Contribution rates of accelerating models to gaseous pollutants are the highest. The contribution rates of CO and NO_X is up to 67.1% and 65.4%. We collected the operating modes and conditions of the engine of test vehicle and confirmed the working range of different cycles. The test contrasts the difference of the engine's working range of the emission regulations cycles and actual travel cycles. The conclusion is that the emission regulations cycle can't reflect the complete-vehicle condition in use.

Through the statistics analysis of serious road traffic accidents over recent years, this study concludes that human error is the major factor causing road traffic accidents. Establishing a cognitive response model to analyze the factor of human error in the traffic system that consists of human, vehicle, road and environment this study puts forward measures to prevent road traffic accidents.

Core Rockfill dam is characterized by huge filling volume, multiple material sources and high strength of transportation to dam, which leads to a higher demand on organizational arrangement of transportation system, as well as on control of material sources on the construction site. Aiming at characteristics and main points of control over the process of materials transportation to dam, the real-time monitoring method of the whole process of materials transportation to dam for rockfill dam is proposed based on monitoring indexes and control criterion using Global Positioning System (GPS), General Packet Radio Service (GPRS) and Personal Digital Assistant (PDA) technology. Real-time automatic collection technology of the transportation process information and calculation and analysis of method of transportation parameters are also proposed. Application in practical engineering shows that mismatching loading or unloading of dump trucks can be discovered in time, wrong filling of dam materials can be avoided using the technology. It can also be used to calculate traffic density and strength of transportation to dam. The technology is an innovation of construction management method for rockfill dam, which has provided strong support for construction quality management and organizational arrangement.

There are two methods for evaluating the energy utilization system: energy balance analysis and exergy analysis. Energy balance analysis is to study the amount of energy conversion, transmission, utilization and losses, and also to determine the energy efficiency of a system or device. Nevertheless, exergy analysis is to judge the quality of different energies - such as high-quality energy and low-grade energy - to make full use of it, and avoid wasting. In this paper, the simulation of working process on a middle-speed diesel engine is performed. With this simulation, the energy utilization is evaluated by the above-mentioned two methods.

With the increase of urban congestion, scholars at home and abroad have paid more attention to roundabouts in recent years, which are important nodes in the urban traffic network. Much of the research on roundabouts included topics such as capacity, security, etc. Headway, an important traffic flow parameter, was also studied by some researchers. However, due to the constraints in geometric condition of roundabout and acquisition equipment, it is difficult to obtain the continuous headway data in distinct locations. Using VISSIM, a single-lane roundabout is built in this paper. Considering the geometric characteristics of the roundabout, some basic parameters of driver behavior in the simulation software are calibrated. Simulagtion experiments under different traffic conditions at four collection points near an approach are made, the results are as follows. The distributions are described in different locations and traffic conditions, and the PDF distributions are given visually with the help of the kernel density estimation method, which shows that it has a distinct headway distribution characteristic with the difference of traffic volumes and collection locations. Then, the average time headway values are analyzed, which indicate a decreasing trend with the increase of traffic flow. A fitting analysis is made between AHV and traffic volumes, and the results show that it meets a quadratic nonlinear relationship, while R² and RMSE prove that it has a good fitting effect. This paper proves the practicality of VISSIM in roundabout study, and also discusses the relationship between traffic volume and headway, which provides a beneficial trial for roundabout research.

Lack of detailed land use (LU) information and inefficient data gathering methods have made modeling of urban systems difficult. This study aims to develop a hybrid remote sensing (RS)/geographic information (GI) system in order to extract residential LU information from very high resolution (VHR), remotely sensed imagery. Land cover information extracted from remote sensing and several types of geographic data from the study area (City of Fredericton, Canada) are fused into the residential LU extraction expert system to examine correlation/association rules at the building level. Morphological analysis at the building level is used through a step-wise binary logistic regression model to provide a set of multi-dimensional indicators for extracting the residential buildings. In this regard, sets of morphological properties derived from geographic vector and remotely sensed data are used in a binary regression model. LU classification from the morphological analysis results in an overall accuracy of 93.2% for extracting residential buildings. It should be noted that equipped with such a powerful LU data collection tool and detailed LU data, urban planners/modellers can more reliably and precisely predict economic interactions, activity locations, space and housing developments, business expansion, and trip patterns.

To avoid delay and minimize the travelling distance of all routes for dynamic vehicle routing problem with time window, the planning horizon is divided and the dynamic vehicle routing problem is partitioned into a series of static sub-problems which are solved by improved max-min ant system. In the max-min ant system, routes are constructed with the parallel and sequential methods for datasets respectively aiming at customers in random and clustering distribution. As the behavior of max-min ant system depends largely on the value of parameters, multi-parameters including distance heuristic factor, choice probability, level of pheromone persistence, level of time window and the number of ants are self-adapted at different stages in the course of algorithm execution. Instances are tested and results show the effectiveness in solving these problems.

Snow- and ice-covered pavements threaten highway traffic safety in the winter. The use of snow-melting agents is one of the most significant means to rapidly remove ice and snow on road. According to the main ingredients, the highway snow-melting agents are classified into three types: chloride salts, non-chloride salts, and environment-friendly ones. Comparisons on the melting snow and ice performances are conducted on the aspects of their melting ice and snow performance, the corrosion to the concrete and metal materials, the effects of poa pratensis seed germination percentage of different snow-melting agents to evaluate different agents' performances synthetically. The test results show the differences among the different snow-melting agents on the aspects of technology, environment and cost. The applicability of the different snow-melting agents is summarized. Finally, the technological references are proposed to guide using snow-melting agents efficiently, safely and in an environmentally-friendly way.

Knowledge of departure times of commuter trips plays an important role in providing a basis for future policy making and for forecasting the peak hour without a great deal of investigation. This paper has proposed a departure time choice model based on prospect theory, considering that travelers are not entirely rational (i.e., being affected by the environment, the ability to obtain traffic information, and so on). In the case study, travelers are divided into several groups by their risk attitude (risk averse, risk neutral, risk appetite). We then find the differences in the departure time amongst different the kinds of travelers, providing evidence for road network construction and traffic management.

A hybrid genetic algorithm for solving vehicle routing problems with time window (VRPTW) is presented. The proposed heuristic adopts a new chromosome structure containing more information about the vehicle route configuration. Computational experiments are implemented to verify the performance of the proposed hybrid genetic algorithm, and the solutions are competitive to those published in literature.

In order to rule overload and oversize transportation, and to regulate the production of vehicles, mandatory standard GB 1589-2004 ("Limits of Dimensions, Axle Load and Masses for Road Vehicles") was promulgated and implemented in China. The expected result was achieved with the implementation of standard GB 1589-2004. However, with the improvement of vehicle technology, road and the facilities, related technical regulations should more closely conform to international regulations. Besides, some factors which didn't meet actual situations were found after the implement of this standard. A comparative analysis was discussed in this paper about the dimensions, axle load and masses of vehicle in order to make the standard more suitable for road transport's actual needs, road facilities' requirements at home and abroad. Finally, this paper puts forward opinions and suggestions which will be useful for the revision of the standard.

Tunnel is prone to engineering accident location and the monitoring system can complete the vault subsidence monitoring, surrounding displacement monitoring, steel support stress monitoring, anchor stress monitoring and surrounding rock pressure monitoring by the various sensors. After getting the data, the system realizes the remote wireless monitoring by the GPRS. It can provide scientific basis for the safety construction and normal operation of Yichang to Badong freeway. It has many advantages, namely, all-weather automatic monitoring, and background processing, and information remote real-time transmission.

Over-track buildings are widely adopted along metro lines for their superiority in intensive land use and considerable economic benefits. However, the frequently moving subway trains create large vibrations to the over-track buildings and lead to the discomfort of the occupants, especially for tall buildings. In this study, the measurement of vibration acceleration at the bottom of the columns near the railway lines, which was induced by trains driving into the car depot, was used as the vibration input of the structure. The dynamic response of the upper building was calculated by the uniform excitation method without considering the soil-structure interaction. Based on the evaluation methods presented by ISO 10137 and BS 6472-1, the vibration serviceability of the building was evaluated with the help of MATLAB programming. The results showed that the vibration serviceability of the building cannot meet the requirements and some vibration reduction measures should be taken. The research results are valuable for the finite element modeling, vibration serviceability evaluation of similar engineering.

The activity-based travel demand model has been viewed as an advanced approach with higher fidelity and better policy sensitivity. This study aims to compare modeling results from an activity-based model (ABM) developed using the travel diary data collected in the Tampa Bay Region with an existing traditional four-step model - the Tampa Bay Regional Planning Model (TBRPM), based on the four sequential steps: trip generation, trip distribution, model split, and trip assignment. The comparison results show salient differences. Trip production rates calculated from the travel diary data are found to be either double of or a quarter less than the TBRPM. On the other hand, trip attraction rates computed from ABM are found either more than double of or one tenth less than TBRPM. The trip distribution curves from the two models are found similar, but the peaking of travel time is different, with 10 min for the TBRPM, but 15 min for the ABM. Mode split analyses show that the TBRPM may underestimate the driving trips and it cannot capture the usage of other alternative modes, such as taxi and non-motorized. In addition, the ABMs are found to be less capable of reproducing observed traffic counts when compared to the TBRPM, most likely due to not considering the external and through trips. The comparison results presented can help transportation engineers and planners better understand the strengths and weaknesses of the two types of models and this will subsequently assist decision-makers to choose a better modeling tool for their planning initiatives.

As the significant node of modern logistic system and the cluster of logistic industry, Logistics Park has already been considered as a new potential increasing point intended for promoting the progress of urban and regional economics. From the perspective of growth pole theory under the regional economic theory, this paper indicates that the Logistics Park, functioning as an emerging mode for accumulation of modern logistics, is a growth pole for certain cities or regions, and is able to advance and spur the common development of surrounding area, in order to achieve a relatively balanced development of regional economics through the effect of radiation and trickling-down. The analysis made in this study shows that the influence on regional economics due to the operation of Logistics Park involves the following aspects: a) aggregating related logistics industries; b) promoting the reasonable optimizing and configuration of the elements of resources; c) benefiting the training of the third-party logistics market; and d) expanding employment.

In road safety research, it has long become a tradition to take a parametric approach to modeling road collisions, which has resulted in a variety of parametric approaches such as Negative Binomial, Poisson lognormal, zero-inflated Poisson, and random-effect models. While easy to apply and interpret, a parametric approach has several critical limitations due to the modeling requirement of assuming a specific distribution form for each model variable and a fixed functional relationship between each model parameter and the predictors. Violation of these assumptions could lead to biased and/or erroneous inferences on the effect of these predictors on the dependent variable (e.g. collision frequency). This paper introduces a data driven, nonparametric alternative - Kernel regression aiming at answering the question of whether or not it makes any meaningful differences as compared to the traditional parametric method. The proposed approach has been applied to model winter road collisions using a database containing hourly observations of collisions, road weather and surface conditions, and traffic counts on a set of highways in Ontario, Canada, over six winter seasons. The results from this approach have clearly shown that significantly nonlinear relationships exist between collision frequency and some condition factors, which have not been captured in the previous studies that use the parametric technique. Furthermore, the new approach also captures some moderating effects of several condition variables, which could be easily missed in the parametric analysis.

In order to verify the implementation effect and the decision-making rationality of the transport investments in large-scale economic stimulus plan, the application of data envelopment analysis model and related software was used to calculate the changes of the scale efficiency and technical efficiency and comprehensive efficiency of the transport system as the investment target in a period of the large-scale infrastructure construction. Through the analysis of efficiency changes of traffic system, to determine the operation of the traffic system, to evaluate the decision rationality of the transportation infrastructure investment in the economic stimulus plan and making future direction and strength of the investment decision.

Driver fatigue is a hazard which can easily lead to traffic accidents. To detect driver fatigue in real time, a novel fatigue detection system using support vector machine (SVM) based on eye movements is proposed. Eye movement data was collected using the SmartEye system in a driving simulator experiment. Characteristic parameters which include blinking frequency, gaze direction, fixation time and PERCLOS were extracted based on the data using statistical method. The characteristic parameters were used to train and test SVM model. Experimental results show that this system achieves a satisfied performance, which demonstrate that eye movements can be used to detect driver fatigue in real time.

Night vision enhancement systems (NVESs) have been developed to improve visibility at night through supplementing drivers' direct vision with additional information shown on a display, rather than replacing drivers' direct vision. Existing studies have shown that NVESs may increase recognition distance, but may also increase drivers' mental and visual distraction (eyes-off-road). Each scan of the display of the night vision enhancement system involves some visual and mental cost to the driver. This research focuses on developing an affordable and integrated experimental platform that can provide drivers using NVESs with a realistic nighttime driving experience. Study on both near-infrared (NIR) and far-infrared (FIR) NVESs' overall benefits and driver distraction were conducted on this platform with the purpose of exploring both the advantages and disadvantages of current NVESs and making recommendation for future improvements. Twenty-four experienced drivers from Northeastern University (staff and students) participated in this study of NVESs. They used and tested NVESs systems in the Virtual Environments Laboratory and were required to complete two experimental trials, each individually. Results demonstrated that simulation provides a good opportunity to experience driving with a NVES, and also is a very good tool for conducting research on NVESs, especially in adverse weather conditions like fog.

To develop the Driver Assistance System for foggy weather will help to increase driving safety. This paper will introduce a method based on digital information from computer vision and millimeter-wave radar techniques to build a driver assistance system for foggy weather. The algorithm, which takes advantage of the Direct Liner Transformation method, is to perform image registration between the object ahead detected by millimeter-wave radar with a vision enhanced scene in foggy weather. The information based on millimeter-wave radar and digital image will be used to help drivers to drive with good vision. The experimental results showed our Driver Assistant System is robust, the automatic registration is accurate.

With the increasing interest in Intelligent Transportation Systems (ITS), the construction of traffic data collection systems in many cities has expanded in recent years. All these data have built a good basis for the urban traffic managers to better understand the real traffic conditions and future developing trends. Trying to use these data well in this way, Shanghai Traffic Information Management and Evaluation System (SHTIMES) has been developed in Shanghai, China. The objective of SHTIMES is to integrate all the collected data from different sources and give a reasonable traffic operation evaluation so that the corresponding traffic managers can make their decision based on that. Three key aspects during SHTIMES development are addressed in this paper: Firstly, in the data collection aspect, the "closing ring" scheme is adopted for the surface road network, which can infer all the traffic flow over the network; secondly, in the model part, a united evaluation model for all the urban roads is introduced; finally, a C/S structure is used in the system design. All the functions related to calculation and are assigned to the server end and all the functions related to the information management and analyses are assigned to the client end.

One of the major problems that limits the practical realization of the Intelligent Transportation System is collecting and distributing transportation information rapidly and effectively. Aside from traditional passive means, mobile devices (such as smart phones) could be exploited to collect various types of transportation information from individuals in massive quantities interactively, as well as delivering guidance and navigation signals to the public to achieve purposes like congestion avoidance. This paper proposes a Mobile Transportation Information Service System (MTISS) which integrates client-end applications with SOA-enabled server-end web services. A unified, loosely-coupled and scalable architecture is presented. Then, a prototype on Android platform and Windows Communication Foundation (WCF) is implemented. The key techniques are discussed. Application scenarios and the features of MTISS are addressed. Finally, experiments are conducted to evaluate the overall performance of the MTISS prototype and the results indicate that our system has high usability, scalability and efficiency.

Variable message signs can display a variety of information, and the text layout is one of the factors which affects the driver's visibility. This paper studies the impact of the arrangement, letter spacing, and line spacing of the text of variable message signs on driver recognition time. The results show that word structure is the most important factor affecting recognition time. A shorter recognition time was achieved when the same word was displayed along one line as opposed to two. In addition, if the impact of word structure is not considered, a shorter recognition time resulted when the same phrase and text was displayed in an arrangement of two lines instead of one or three lines. When text spacing is increased, the recognition time first decreases and then increases; with the increase in text line spacing, recognition time reduces.

As a form of expressway direction information, there are no complete rules for urban expressway exit numbering in China. In addition, the national standards do not list rules for the marshaling method of urban expressway exit numbering. Referring to relevant rules stated in the national standard, "Road Traffic Signs and Markings", as well as comparing and analyzing the current situation of expressway exit numbering in Beijing, Shanghai, and Guangzhou, this research proposes marshaling rules of expressway exit numbering on the basis of the demand for directional sign informationization, current expressway types in China, and construction scale in different cities. The goal of this study is to provide drivers with the only and correct exit information to help them identify and confirm the exit position of their destination in the shortest time, allowing them to exit the expressway safely and smoothly.

There is no fault-tolerant design in Automatic Identification System (AIS) data link, so the fault message is inevitable. The DS theory is able to simulate the artificial judgment on AIS messages, but the motion and lane evidences conflict with each other occasionally. The improved evidence similarity method would solve the problem, simulate human thinking, take the evidence priorities as a new parameter to revise the combination, and improve the model. In field testing, the method shows very good performance.

In car navigation applications, the real-time parking information is an important application for the future; but, there is no standardized definition for the communication data model of the real-time parking information. The specifications are defined for the real-time parking information, where they are mainly expressed in terms of whether the parking is full or unoccupied, the parking jam information for the exits, fee information, as well as parking information. The three-layer model is defined for the information dissemination to express the different detailed levels parking information.

The paper aims at illustrating how the biometric data (such as the heart rate or the skin perspiration) of a mobile user taken by commercially available systems may be stored through a Bluetooth interface on the user mobile to be processed using a simple expert system that takes into account the possible pathologies and the current activity of the users to elaborate a first health diagnosis, helping the remote medical centers to decide the equipment type in the ambulance and the doctor specialties. Also, the paper points out how integrating the traffic information taken by various technologies and from people's perceptions is possible to compute, in real time, the travel time of each road to find the minimum path to the accident position.

Fixed and moving facilities on the highway are implemented to form a network by the internet of things. A technology of radar chain detection and screen information confirmation on the highway is proposed to identify and analyze highway accidents and then determine the influence area. Emergency response and rescue can be carried out by Mechanism of Highway cross-department emergency and linkage management. At the same time, a partition and classification publishing model of traffic accidents information and traffic Induction information is found to carry out public information services and induce other travelers to avoid traffic accidents in the region effectively. The Highway traffic accident identification and emergency response technology based on the internet of things has been applied on the highway of Anhui, China. The effect is obvious. It will play an important role in improving highway safety management services.

The communication quality of a vehicular network is confronted with great challenges due to a surge in vehicle numbers, as well as the high mobility of vehicles on the road. Network coding technologies can improve network performance in terms of higher throughput, reliability, and robustness. In this paper, we generally consider the characteristics of vehicular communication, network coding, and cooperative communication and study the methods of outage probability analysis in a vehicular cooperative network. Based on this, we propose a novel mobile dynamic relay selection strategy with network coding and also derive the expressions of diversity gain and channel capacity. Finally, we conduct simulation experiments with different scenarios to verify the proposed strategy. The theoretical analysis and simulation results show that the proposed relay selection strategy can effectively reduce the outage probability, improve the system diversity gain, and expand the system capacity.

As the combination of Internet of Things and transportation, the research for pedestrian or vehicle traffic information collection have been carried out. This paper shows the concepts and methodologies of Bluetooth signal collectors, which can collect real-time Bluetooth signals from portable electronic devices such as intelligent cellular phones, PDA, Bluetooth headsets, etc., within its coverage. In field application, Bluetooth signal collectors are distributed to fixed points in the traffic network. Based on the matches of uniform Bluetooth MACs in time series, the traffic parameters can be collected precisely. After programming design, circuit design and electronic components selection, sets of prototypes were developed. Then, groups of experiments were carried out and the detection rate of the collector prototype was found to be 85% with self-antenna. Furthermore, the influence factors for missing signal detection were summarized. Based on the research, the Bluetooth signal collectors were applied in field pedestrian traffic survey at metro transfer stations squares. It is concluded that important parameters of pedestrian traffic can be collected and calculated accurately, including the arrival and departure distribution of tourists, the transfer ratios and transfer time, which are essential for refined traffic planning and management.

This paper is aimed at increasing the demand of real-time access and application services. An Internet in vehicles system based on On-Board Diagnostics (OBD) technology and android platform was proposed. This system was composed of a data acquisition device, an android smartphone, network access and a remote service center. Through the OBD interface interacting with the vehicle, the vehicle identification number (VIN), mileage, and condition information can be obtained, which could be used for vehicle identification and effective vehicle condition monitoring and control. The intelligent navigation services using GPS, AGPS, and INS based on an android smartphone was provided so the corresponding man-machine voice interaction and network data switching could be achieved. The results of the experiment indicated that the system can effectively provide data sharing, intelligent navigation, and remote fault diagnosis services, which can meet needs of the real-time capability and applicability of the Internet in vehicles system.

With the development of urbanization and social progress, the traffic problems become more prominent. How to manage the transportation system effectively and achieve efficient flow of vehicles is a major issue facing contemporary society. In recent years, with the Internet of Things technologies rising quietly, it promotes the rapid development of the intelligent information service industry. Through the Internet of Things technology application and innovation in the field of intelligent transportation and logistics, it can provide a new information technology intelligent management mode for the transport system. Through analysis of the Internet of Things technology, this paper elaborates on the link between the Internet of Things and the Intelligent Transportation; the focus on objects associated transport new platform, including intelligent information service, vehicle identification, vehicle navigation and positioning; the best path selection, traffic information release and build transportation information integration system to improve the road utilization and the efficiency of traffic running; realize intelligent management of traffic; and finally achieve intelligent transportation.

Traditional bus arrival time prediction such as Artificial Neural Network (ANN) and Support Vector Machine (SVM) is based on large-scale data mining. Due to the real-time and uncertainties characteristic of traffic conditions, the method based on historical data mining cannot predict bus arrival time accurately. This paper presents a real-time prediction method based on probe bus fleet models. The probe bus fleet is established by all the buses running on the bus line. The bus line will be separated into different meta-segments because of the overlap of different bus lines and etc. The bus fleet should be established and disassembled dynamically based on the meta-segment, and the real-time data collected from probe buses could be used for next bus arrival time prediction by using the Kalman filtering technique. Experimental results show that this model provides a higher level of veracity and reliability of travel time forecasting in the case of frequently changing traffic conditions, and support real-time adjustment to obtain more accurate bus arrival time.

Vehicular Ad-hoc Networks (VANETs) are well known for their fast-changing topology and adverse wireless channel environments. This paper studies the problem of competitive joint channel and bandwidth allocations in multi-radio multi-channel wireless networks for VANETs scenario. Existing works only study competitive multi-radio channel allocation and do not consider two important issues, impact of channel traffic load to transmission quality, and variability of packet arrival rates in links of different node pairs. In addressing these two issues, we extend the problem of competitive multi-radio channel allocation to competitive joint channel and bandwidth allocation. We model the problem as a non-cooperative static game, called joint allocation game. Using the best response concept, we prove existence of pure Nash Equilibriums (NEs) for the joint allocation game. We also investigate efficiency of NEs allocation in the joint allocation game. We design two distributed algorithms to enable node pairs to converge to NEs. These two algorithms are evaluated through extensive simulations. The results show that our algorithms can improve system throughput by 2 or 3 times compared with solutions for competitive multi-radio channel allocation.

Considering the existing problems with the road maintenance management system in China, in this paper, we put forward and develop a maintenance system based on the ArcGIS Server and WebGIS technologies. This study aims to further promote the informatization and spatial visualization of the maintenance system according to the application demand of the road management department. Maintenance management data can be presented in forms of intuitive maps in the experimental system, and the system provides an efficient, integrated management of spatial data. The proposed system addresses the problem of data sharing and visual display, while also providing effective solutions for data organization and management of roads and offering data support for the pavement maintenance system. In this paper, we present a maintenance management experimental system in the .NET environment and the ArcGIS Server platform, taking maintenance data in the BaNan district of Chongqing Municipality as an example.

The traffic information based on GPS/COMPASS is widely used in the intelligent transportation system. The security of traffic information transmission has many challenges that are presented in the paper. It designs a security scheme for message transmission between the vehicle and the data a collection server and between the data collection server and the traffic management center. It indicates the realization of the security scheme. The security scheme ensures the integrity of the data and implements mutual authentication among the vehicle, the data collection server, and the traffic management center using X.509 certification.

From a systematic perspective, IDEF methods, adapted to the complex systems, are utilized to build up the model of intelligent transportation system (ITS) and make functional analysis and information analysis under internet of things (IOT) circumstances. The function modeling on IOT-based ITS is established based on the method of IDEF₀, and the information modeling on IOT-based ITS is built up by the method of IDEF_1X. A systematic and structural method is provided for IOT-based ITS modeling and the system function and information process analyzing.

To relieve the parking problem caused by the increasing number of vehicles, the urban parking guidance system based on Radio Frequency Identification (RFID) has been studied. The proposed system can collect information about cars by RFID, receive and handle the information, and then offer optimized scenarios to guide cars into the suitable parking places. In this way, it will help to save parking time, improve the utility ratio of the parking spaces, and decrease the possibility of traffic jams caused by searching for the parking spaces.

The high cost of video-based anti-collision warning systems is just one shortcoming of this traditional method. By analyzing bridges in hazardous areas, we can extract various factors affecting bridge collisions and propose the key factors of the initiative anti-collision warning system, thus simplifying the bridge initiative anti-collision model. This new type of independent warning system was implemented for a large bridge in the Xiangjiang area. This new warning system has the advantages of low cost, system stability, high reliability, and ease of use.

With the rapid development of highway construction, the proportion of tunnels became larger and larger. So, automatic fire detection is very important for long tunnels and tunnel groups. In order to reduce the false alarm rate and increase system reliability through analyzing the current all kinds of highway tunnel fire detection technology, the scheme for highway tunnel fire automatic detection system was presented based on double detectors and BP neural network, and which perform alarm linked with tunnel video surveillance system. Practical application shows that this system increased the response speed and accuracy of fire detection and promoted emergency rescue plan implementation efficiently.

As the parking demand in the urban centers located in the Frigid Zone is significantly affected by the climate, a parking demand prediction model based on random utility theory and consideration of different influencing factors is put forward in this paper in order to analyze the parking behavior. First, the model of the relationship between the static traffic demand and travel generating purposes is established. The model takes the ice and snow into account as factors affecting travel behavior. Then, the traffic volume prediction function, based on the traveling utilities of residents, is presented. Ultimately, the static traffic demand prediction model resulting from analysis of the residents' behavior in the considered area is accomplished.

Most current license plate detection (LPD) systems target only the vehicles in a single lane or at a short distance from the camera (i.e. each frame contains only one vehicle). Most of these systems utilizing edge features to detect license plates on distant multi-lane vehicles directly would fail because there are many edge features and the edges of the license plate would be interfered with by different types of vehicles and the background. In this paper, we propose a hierarchical approach that detects individual vehicles first, locates the region containing the license plate, and finally extracts the license plate. To verify the effectiveness of the proposed system, four-lane and two-lane video samples were used for testing. The car detection rates were almost 100% for both the two-lane and the four-lane videos. The LPD rate was 85% for the two-lane video and 92% for the four-lane video.

Along with the traffic video widely used by the intelligent traffic system to monitor the vehicles, their information (such as the license plate), the vehicle type, and so on, is successfully acquired. However, if the traffic video has impulse noise, none of the above systems can get the satisfied results due to the noisy sensor or channel transmission errors. Therefore, it is necessary to suppress the impulse noise. Although the classical median based method has been widely used to suppress the impulse noise in recent years, the noise suppression and the detail preservation result cannot be satisfied due to the noise filtering on each pixel in the whole image, no matter whether or not the image pixel is corrupted by the impulse noise. This paper proposes a novel median and switching based method to detect the impulse noise, with the detected impulse noise replaced as the evaluated value and the detail pixel protected as the original value. Experimental results on the testing image and the traffic video image show that the proposed method can work better than other methods in both the quantitative and qualitative aspects.

Since foggy days are hard to forecast, the probability of a traffic accident happening on these days will be several times more than that on the usual days, highly reducing the traffic safety and greatly causing economic losses. In addition, dense fog is the main cause of multiple vehicle collision accidents. Since the traffic monitoring technique has been widely used in the traffic management, removing fog from the traffic video has become the hot research topic in recent years. First, this paper reviews the retinex method, commonly used to remove the fog in the traffic management. Then, it proposes the improved retinex-based method to remove the fog in the traffic video. Experiment results show that the proposed method can not only remove the fog but also enhance the clarity of the traffic video image.

In this paper a control delay model with queuing profile is presented. There are two major performance measures regarding signalized intersections: control delay and maximum queue length. Most control delay models are derived from the vehicle cumulative counting curves whereas most queuing profiles at signalized intersections are based on the vehicles' temporal-spatial diagram. Since the control delay and queue length are highly correlated, there is a need for an integrated model which considers the control delay and the queuing profile together. We started from the conventional vehicle cumulative counting curves and then superimpose a dynamic queue-end curve based on the queuing profile. From the arrival, queue-end and departure curves, the time points when an individual vehicle joins the queue, moves again and passes the stop line can all be calculated. The dynamic queue length over time and average control delay can be derived as well.

Traffic detection and collection techniques have rapidly developed in recent years. Detectors - such as coils, infrared, ultrasonic, and video - as well as GPS locating techniques have been widely used to build a variety of traffic data collection systems. The Bluetooth technique, as a relatively new detection and collection technique, plays an ever more important role in traffic information collection. With the development of the Bluetooth technique, related products are also more abundant. This paper establishes a traffic information collection system based on Bluetooth and lists the physical structure, software structure, and work procedure of this system. Based on an in-depth study of Bluetooth and the micro-controller principle, this paper develops Bluetooth-based traffic information collection software using machine language and achieves the function that road Bluetooth detection devices can search the address of a car Bluetooth device. After the processing of traffic information data, we can determine values of travel time and average speed. Furthermore, we can assess the real-time traffic situation with the indicator of road average speed. Finally, the case study proves the advantages of the traffic information collection methods based on Bluetooth and discusses the installation layout of Bluetooth detection devices in different road forms. The Bluetooth technique in traffic detection provides a strong basis for further transportation planning, traffic control and management.

Currently, the minimum time path-finder software packages reside on the user navigators or on a main urban server, but compute the minimum paths using statistical travel times. However, such paths are not always the best ones and, consequently, a software is envisaged which uses the current road travel times. Since such navigational and monitoring software may cause a very high server load, the paper aims at illustrating an alternative solution obtained with driver mobiles able to compute both the services suitable for the drivers and the best current paths to reach them, with a limited intervention of the server. In particular, a distributed computing scheme consisting of a navigational and monitoring software resident on the server integrated with a navigational package implemented on the mobiles is presented. A case study clarifies how the proposed solution helps both drivers and pedestrians.

Highway agencies have gathered traffic data for a wide range of engineering and management purposes since the early days. Traffic data is the foundation of decision-making related to the planning, design, operation and management of highway transportation system. The British Columbia Ministry of Transportation and Infrastructure (BCMOTI) in Canada has collected traffic information for various engineering and management purposes since the earliest days of the province. This article describes the BCMOTI traffic data collection practice, which includes a review of traffic data needs, traffic monitoring procedures and methodologies, and a corresponding economic analysis. Transportation agencies have developed their programs independently and BCMOTI's experience indicates that more economic alternatives with equivalent or better accuracy are available. BCMOTI has strived for excellence in its traffic monitoring practice, and those activities are also highlighted and reported.

Highway agencies have gathered traffic data for a wide range of engineering and management purposes since the early days. Traffic data is the foundation of decision-making related to the planning, design, operation and management of highway transportation system. The British Columbia Ministry of Transportation and Infrastructure (BCMOTI) in Canada has collected traffic information for various engineering and management purposes since the earliest days of the province. This article describes the BCMOTI traffic data collection practice, which includes a review of traffic data needs, traffic monitoring procedures and methodologies, and a corresponding economic analysis. Transportation agencies have developed their programs independently and BCMOTI's experience indicates that more economic alternatives with equivalent or better accuracy are available. BCMOTI has strived for excellence in its traffic monitoring practice, and those activities are also highlighted and reported.

Vehicle classification is one of the main focuses in traffic survey work. In this paper, an influenced recognition model of vehicle class was proposed and experimented on using the feature extraction of vehicle's time-domain sound signal, considering the existing problems like costly equipments, low efficiency in operation, and difficulty of data analysis, etc. According to vehicle's sound signal waveform characteristics, it is shown that the changed point can be obtained by analyzing the short-time energy and zero-crossing rate in time-domain, and then the vehicle class can be determined. The simulated experimental results indicate that the proposed method is simple and economical to recognize vehicle class. The statistic precision can correspond with the need of the engineering.

Due to its significance for advanced traffic management systems and traveler information systems, travel time estimation is usually selected as the objective for optimal freeway sensor density. Unlike most existing studies focusing on the homogeneous traffic flow, this paper develops a method with the consideration of multi-class traffic flow. The multi-class LWR model is used to depict the traffic dynamics, particularly the shock waves. Then, the approximate travel time can be obtained with such approach as midpoint method, and the optimal sensor density can thus be derived. With this work, it will be useful to the sensor location problem for multi-class traffic flow in real freeway management systems.

In ITS field, short-term traffic flow forecasting is one of the key technologies for traffic control and guidance. One kind of short-term traffic flow prediction method based on the improved non-parametric regression model is proposed in this paper. In this method of distance metric criteria, the Dynamic time warping distance is used instead of the traditional Euclidean distance as the prediction method. Using the non-linear alignment of each point between two sequences to calculate the similar distance, it can overcome the matching problem caused by the expansion and contraction of time series in timeline, and get a better forecast result. The performed simulation based on the traffic data of Xiamen Lotus junction cross-section shows the lower prediction errors that indicates the feasibility of this method.

Pedestrian detection in complex scenes is a key challenge in traffic detection by video. A newly designed, embedded pedestrian detector based on the kernel TI's DSP chip (TMS320DM642) is proposed. The detector adopts the Hausdorff distance template-matching algorithm for pedestrian detection and tracking. The framework of the algorithm and its DSP optimization procedure is described in detail. The results of a real crossing experiment indicate that the detector is able to rapidly detect pedestrians in a complex traffic scene with 95% precision.

This paper puts forward a new coordination control model of entrance ramp metering integrated with upstream intersection signal control. Based on the improvement of Mixed-Control algorithm, the Color Petri Net (CPN) is used for verifying the feasibility of coordination control model in conflict, dead lock and activeness aspects. VISSIM simulation is applied to test the effectiveness of this coordinative control method on entrance ramp of northwest 4^th Ring Road of Beijing. Simulation results show the traffic control performance of ramp queue length, average queue time, occupancy and delay time can be greatly improved.

The accurate acquisition of traffic state data is the most important aspect of Intelligent Transportation Systems, which can effectively solve traffic problems such as traffic jams and traffic safety. Though the technology for acquisition of traffic state has developed greatly, problems such as data invalidation still exist and have not been effectively settled. The concept of the road traffic information templates is thus put forward in this paper. The road traffic states are divided into several different modes, and data from road traffic detectors are extracted to obtain road traffic information templates. The conditions suitable for road traffic information templates are also discussed in this paper. Finally, two typical expressways in Beijing are adopted for the application of the road traffic information templates. The results prove that this road traffic information templates approach is feasible in the area of traffic state estimation.

In order to better describe the travel route choice behavior in uncertain environments, a travel route choice model was proposed under the conditions of real-time traffic information. Based on the cumulative prospect theory (CPT), it analyzed the psychological characteristics of travel route choice behavior. Considering the release of real-time traffic information in route, it specifically designed the principle and process of travel route choice model based on cumulative prospect theory. Additionally, it used examples to comparatively analyze the travel route choice behavior under the theory of traditional expected utility (EU), adjusted EU and CPT. The results indicated that the CPT is able to overcome many shortcomings of EU theory, so it is a better description for decision-making process of travel route choice. The release of real-time traffic information allows travelers to update travel time in real time, adjust path in route as well as realize the dynamic route guidance.

In the process of predicting link travel time, the difficultly of handling high-dimensional and nonlinear data consistently poses problems to researchers. Because the single least squares support vector machine cannot handle these issues, a prediction method based on wavelet package analysis and least square support vector machine was proposed to forecast link travel time. The verification results obtained from VISSIM simulation data show that the link travel time prediction method is better and has definite application value.

Nowadays, traffic flow prediction has become a hot issue in the traffic areas. Because of the uncertainty, short-term traffic flow prediction is quite difficult. The Radial Basis Function Neural Network has local generalization abilities and fast convergence speed. Using this method, we can obtain higher prediction accuracy within a relatively short time. Meanwhile, combination with the flocking theory can improve the efficiency and accuracy of calculation. After the simulation experiments, it shows that this method is quite effective.

A traffic survey and analysis was conducted in the section parking that surrounds the school. Additionally, the traffic flow parameters were calibrated and an accumulation and dissipation model was established which was based on the swarm theory. Furthermore, several experiments were simulated at the same time. The validation shows that it is well fitted. Finally, it was proposed that the improvement scheme of the parking surrounds the school.

Forecasting the transfer volume based on time-phase can provide a scientific basis for operation scheduling of different traffic modes. It can improve the coordination of transit of different traffic modes. This paper is based on the information collection of the passengers' transfer behavior in Liaoyang Passenger Transport Hub and analyzes the differences of the changes of passengers' transfer behavior according to the time-phase. It sets the transfer behavior between every two traffic modes as the objective and builds the Logit model of the passengers' transfer distribution. The paper analyzes the influencing factors of passengers' transfer decisions in different time-phases based on the results of parameter calibration. This research combines the theory with the passengers' actual behavior and provides a new way of analyzing the transfer volume forecasting.

With the popularity of mobile positioning devices, large numbers of multi-source Points of Interest (POI) and road data are increasingly collected resulting in a crucial problem when integrating these heterogeneous data. The paper thus proposes a geometric-based approach for integrating multi-source urban POI and road networks. The proposed method firstly extracts the linear features from POI data according to a DBSCAN-based linear clustering algorithm and then generates a graph structure, named POI Connectivity Graph (PCGraph). The matching nodes between PCGraph and road network are then selected by the probabilistic relaxation framework and then refined by the vector median filter to align POI data and road networks geometrically. The experiment shows that the linear extraction algorithm efficiently identifies the inexplicit structural patterns of POI data and the probabilistic relaxation matching approach correctly finds the corresponding points to efficiently accomplish the position adjustment of POI and road data.

Considerable errors exist in speed data that is obtained from various detectors, and its accuracy directly affects the results of various traffic analysis models. This research implemented 12 groups of field experiments on roads of different classes by using a test vehicle with GPS modules. It attempts to verify the accuracy discrepancy of travel speed data collected by a floating car system, microwave detectors, and loop detectors. Analysis shows that the average travel speed errors of floating cars on road sections of urban expressways and arteries are 13.6% and 27.8%, respectively, and the collected data and the actual speed have the same distribution. Compared with actual speed, the errors of the microwave detector on expressways and loop detectors on arteries are 30% and 56%, respectively. Although there exists a certain degree of error, basically, it can characterize the traffic conditions on the road section when the road section speed of the microwave detector is used to denote the travel speed. Study results provide suitable data sources for different traffic models that have different accuracy requirements. Besides, it provides a theoretical basis for improving data accuracy and completeness by using the redundant information of multi-source data. As the traffic congestion becoming increasingly serious, accurate and timely releasing of traffic information as well as reasonable traffic forecasts and guidance have gotten more and more attention. As one kind of the most important data of the Intelligent Transportation System, the accuracy of road section speed directly impacts the ITS application effect. Many kinds of detectors have been used for collecting road section speed, and the three most common are the floating car system, loop detectors, and microwave detectors. The floating car system can provide road section speed, but its accuracy has not been systematically validated. Currently, the literature (Jiang, Chang, Zhang 2009) just validated the accuracy of a single test vehicle by using different time intervals and upload times, but it wasn't for the whole system. Literature (Hu and Wen 2008) compared taxi speed and the travel speed of traffic flow by using the vehicle license plate method that theoretically obtained the precision of the floating car collection method, but it didn't involve the actual accuracy validation of the floating car collection system. Making the Beijing floating car collection system as the research object, by using a test vehicle, this research verified the accuracy of the system and analyzed the error distribution as well as the reasons affecting the data accuracy.

This paper presents a method of estimating the travel demand and vehicle miles traveled (VMT) in large regions including local roads and states. Verification of the procedure is developed for the Indiana Local Technical Assistantship Program (Tarko 2012). The model calibration and evaluation is presented for example parts of Indiana State. In the traditional approach, a network demand model includes properly calibrated traffic generation components applied to Traffic Analysis Zones and traffic exchange relationships between these zones calibrated based on household survey results. This paper attempts to calibrate a model that does not use the household survey but, instead, uses carefully chosen exploratory variables. The model is founded on a number of simplifying assumptions allowed by disaggregation of a large regional road network into much smaller parts called clusters. The network demand estimation could be then conducted for each cluster separately. The traffic generation parameters were fitted with a heuristic search method (genetic algorithm), and the values of exploratory variables (number of residents, employees, etc.) were obtained from microscopic GIS data. The calibrated model was evaluated by comparing the estimated daily traffic volumes with the values obtained from vehicle counting. This paper presents the model assumptions and the results obtained for a sample part of the road network.

Vehicle trajectories provide valuable information of traffic dynamics. The paper proposed a modified video-based trajectory data processing approach to reliably and efficiently collect trajectory data on congested urban roads or at intersections. The approach is on the basis of Knoop's idea of video transformation so that traces of vehicles are visible in a single image. Different from the existing method, a mode-based background subtraction algorithm is applied in the RGB color space to alleviate the influence of a small gap. Vehicle trajectories are then directly detected by searching connected components in the segmented binary vehicle trace image. Test results show that the complete process procedure of a single lane can be finished in 1 hour for a 5-min video. Almost 97% of the trajectories can be accurately detected which is very promising.

The prediction of the incident duration is an important issue to the advanced traffic incident management. An accurate prediction of incident duration contributes significantly to making appropriate decisions to address incidents for traffic managers and obtaining traffic information for travelers in a timely manner. This paper analyzes several regression methods, such as the principal component regression (PCR), partial least square regression (PLSR), and builds models between incident duration and its influence factors. The models were established for three types of incident, correspondingly, i.e. stopped vehicle, lost load, and accident. The models received the best prediction accuracy of 83.6%, 92.7%, and 88.2% for stopped vehicle, lost-load and accident at error for 20 minutes, respectively. The results indicated that the regression method is a promising application to predict incident duration and the PCR and the PLSR have a better performance.

Currently, there is a variety of traffic flow data detection devices. For the limit of the measurement precision of the devices, the traffic flow data from one kind of device is usually inaccurate. The fusion of the data from multiple kinds of devices can improve the accuracy. A data fusion algorithm based on the multi-attribute decision is proposed, with all kinds of detector data as the decision scheme, measurement precision, deviation to the historical average, and deviation to the average as decision attributes, which establishes a decision matrix to determine optimal fusion value. Meanwhile, a traffic state identification method based on fuzzy inference is proposed, which constructs the fuzzy relationship among flow rate, occupancy, and traffic state to estimate traffic state. The experiment shows that, through the application of the data fusion algorithm and the traffic state identification method, the detection accuracy of traffic flow in the test sites is increased by 8.1% and the estimation results of the road traffic state is very consistent with the actual situation.

Currently, in China, the single-objective optimization methods are commonly used for road intersection signal control, which has one single objective such as minimizing the number of stops, average delays, or queuing length. When the intersection traffic varies large with the time of day, using this method for intersection traffic control will always cause poor adaptability and low efficiency. To solve these problems, a multi-objective optimization method for signal control of single intersection is proposed, with the composite optimization objectives to minimize the average delay, the least number of stops, and the shortest vehicle queue length, which can set preferences of various optimization objectives to adapt to different traffic conditions. The method uses the Pareto multi-objective evolutionary algorithm to optimize signal timing parameters to get the best signal control plan. Simulation results show that this method can significantly improve the adaptability and efficiency of the intersection traffic control.

Arterial roads are the aortic mainline connecting urban traffic. Because the traffic demand is huge, often leading to sectional traffic congestion, intersection bottlenecking is the main cause of traffic congestion. By collecting arterial intersection traffic flow data, we analyze the factors affecting intersection efficiency, and propose the sub-region classification method for arterial roads based on intersection factors. On the basis of the sub-region area defined, we propose the dissipated congestion strategy for road and arterial intersections to ease traffic congestion. Based on the multidimensional target of urban traffic management, we design multiple collaborative optimization plans for traffic control of the test road, and use the traffic simulation method to evaluate expected traffic control effect. As a result, we integrated the scientific traffic organization and traffic signal control method and applied them to solve the actual traffic problems, enhance the traffic control performance of urban arterial intersections, and provide a basis for carrying out traffic organization and signal control optimization around the country.

The development of our country's logistics industry is backwards compared with the increasing popularity of online shopping. So, we studied integrated logistics. First, we put forward the influencing factors. Then, we used questionnaires to obtain data and made a preliminary judgment. Next, we built a Logistic regression model to analyze, choosing some variables based on the model through SPSS. Then, we extracted the factors that heavily affect the cooperation between operators and obtained valuable reference data and made relevant conclusions by screening and analyzing the data. Finally, we made some reasonable suggestions.

A novel hybrid method based on wavelet transform and support vector regression was presented to forecast the short-term traffic speed. The method of multi-resolution was applied to analyse stochastic signal in the time series of short-term traffic speed. Considering the non-linear feature in the time series, we used different support vector machines, i.e., ε- support vector machine, ν-support vector machine and least square support vector machine, were applied respectively to the details and approximation from the wavelet transform to establish the hybrid forecasting model. The final prediction result of the hybrid model was obtained by integrating the forecasting results from the details and approximation. The proposed model was realized in MATLAB. Compared with some common SVR models, the performance and prediction results in our experiment demonstrated that the proposed method fitted better to the original data set obtained from real-world traffic speed data, meanwhile it had lower time cost and the predictive accuracy increased visibly.

In order to reduce road traffic interference and the influence of construction on rail metro systems, this paper focuses on the analysis of construction zones and discusses the influence of road capacity on traffic flow organization, including speed limit, truck ban (or bus diversion), and slow traffic facilities. Then, a range of model parameters is explored, introducing the concept of influence degree and establishing the construction section capacity effect model. Several sections of the Wuhan 4th metro line are taken as an example to review the reasonableness of the traffic flow organization rules.

The real-time queue length on signalized intersections is an important parameter for traffic control and management. Based on the analysis of a traffic flow's shockwave profile at the approaches of signalized intersections, a model is built up to detect the real-time queue length based on RFID detector data. Variations of the estimation model are also presented under different traffic volumes, and the relationship between queue length and the capacity of the approach is also considered. A field experiment using RFID Detector Data was conducted at an intersection in Nanjing. The results of the field experiment demonstrate that the proposed models can estimate the real-time queue length with satisfactory accuracy.

Recently, the number of traffic accidents which involve female drivers has been growing. However, there are few studies on dangerous driving behavior of female drivers. After a summary of previous study results all over the world, this paper introduces the concept of "driving quality", its composition, and characteristics. The information about dangerous driving behavior of female drivers caused by "road blindness" is collected using a questionnaire in different regions. The interviewees have different driving experience, age, job, and physical condition (such as menstrual, pregnancy, or nursing period). According to the collected data, the relationship between dangerous driving behaviors and driving quality can be specified which provides the survey method for this study.

An approach to estimate the urban road travel time by using probe vehicle data collected through taxi GPS was proposed, and GPS data correction method of probe vehicle was introduced. According to the poor adaptive ability of traditional filter algorithm in the estimation for traffic state and travel time with Kalman filter, an improved adaptive Kalman filtering method was proposed. The method overcame the shortcomings that the traditional filter couldn't real-time track the change of environment. It could adapt to the dynamic changes of traffic state to realize the optimization estimation. The method was tested on urban roads in Guangzhou, and there was a slight difference between the prediction result and that of actual observation in free traffic flow state and stable flow, and the relative error was under 10% in traffic congested state. The results show that the traffic state estimation model had better tracking ability than conventional Kalman filter.

With the construction of TMIS in the last few years, a reasonable system Net frame with province-centred sections has been built up. But there are still some shortages which can be optimized, such as: limited application scope, incomplete service model, and limited extensible possibility. In this article, the author introduced a cloud strategy concept based on current TMIS frame and researched its value for data analysis on nationwide/public service field strategy making, development of ITS and the application of internet of things. With this concept, some generalized information elements had been decomposed and recombined.

To simulate the traffic on freeway, the stimulus which would influence the drivers' behavior should be quantified. To a certain extent drivers' behavior is dependent on the environmental vehicles' status. In this paper, such influence is quantified by the time to collision. The simulation system is developed in a 2-dimension continuous coordinates system in which the trajectory is continuous and computation cost is larger than general simulation models, which makes the improvement of the algorithm efficiency very necessary. Due to the fact that the relative speed is usually considerable, the dimensions of the vehicles should not be ignored in the collision time calculation. As a result, the calculation process will be a numerical simulation process in which the collision detection algorithm should be applied. A rectangle clipping algorithm is developed and tested for the simulation system in this research.

It is commonly understood that not all highways have the same level of importance in supporting economic and social activities. It is necessary to establish preservation priorities and long-term service objectives to help rationally determine resources allocation. Traffic volumes and road conditions are among the most commonly used factors in defining priority for preservation. These factors cannot directly provide economic explanation to investment decision. This paper proposes the use of road user costs on highway sections to directly link preservation priority to transportation economics. Road user costs are calculated for all highway sections in Saskatchewan and it is found that for some sections, the costs can be hundreds of times higher than on other sections. The fact that road users spend much more on some highway sections is useful information to justify better service. Road user costs are also found to be highly correlated with corresponding traffic volume on highway sections.

This study is part of an effort to incorporate road user costs and economic impacts into asset management system in the network level pavement rehabilitation decision-making process. Widely used software (MicroBENCOST and HDM-4) for calculating road user costs and benefit-cost ratio are evaluated. The outputs generated from the two softwares are analyzed and compared when the input conditions are consistent for both programs. Critical input parameters having dominant impact on major outputs are identified. The evaluation results show that the two softwares have similar changing trend. However, the benefit-cost ratio from MicroBENCOST is normally higher than from HDM-4 under the same input conditions. Engineers should not consider the benefit-cost ratio obtained from either software as an absolute value.

In HINOC system, we use OFDM multi-carrier modulation which is highly sensitive to single-frequency interference. In this paper, notch filter is used to resist such interference. We propose a method to determine the coefficient of the zero-pole IIR notch filter and use the improved zero-pole algorithm with least squares approximation criteria to optimize the pole position of notch filter, so that it has symmetrical and controllable pass-band gain. This method has low complexity, good notch performance, higher processing precision and, therefore, better practical value. Simulations prove the validity of the technique in HINOC system.

A key component to optimizing traffic signals along a corridor with multiple intersections located near highway-rail grade crossings (HRGCs) is an accurate estimate of a given train's arrival time at each crossing. Based on this information, current signal preemption strategies at the traffic signals near the highway-rail grade crossings (HRGCs) could be improved with a resulting improvement in driver and pedestrian safety and transportation system delay. This paper introduces a procedure for the real-time train speed estimation using data from Autoscope video detection and a Doppler radar detector. The two detectors were used in parallel because each, on its own, has a number of issues that preclude accurate detection of simultaneous trains (e.g. trains on different tracks in the detection zone at the same time). A multi-track test bed was chosen for the data collection, speed estimation and verification. A linear regression model was used for calibration of video and radar detection.

Traffic sign detection is an important part of the Intelligent Transportation Systems, and the goal is to separate traffic signs from complex natural scenes quickly and accurately. This paper proposes a method based on adaboost classifier for haar-like features and linear discriminant analysis (LDA) to detect the traffic signs. 1980 positive samples and 4017 negative samples were trained in offline status to provide a rough classification of the interested region in image. Finally, LDA was used to determine the category of interested regions of traffic signs. The method mentioned in this paper has been proved to be effective through static tests and unmanned vehicle tests equipped with independent research.

The topology structure has very important influence on the connectivity reliability of the main corridors network. The local transport network will fail when it is destroyed by traffic jams, natural disasters or human vandalism. Thereby, the transport capacity and efficiency of the entire network will be affected. In order to build a complex network model - which contains four statistical characteristics values constituted by characteristic path length, clustering coefficient, degree and degree distribution and efficiency - the characteristics of main corridors network will be analyzed with the standpoint of a complex network. At the same time, in order to evaluate the connectivity reliability of main corridors network facing two aspects of the attacks - random attack and selective attack - a case for Jilin City will be used.

GPS-enabled mobile phones are becoming more popular and have the potential to be substituted for standalone GPS devices in household travel surveys. In this paper, a set of experiments was designed to evaluate the feasibility of data collection via GPS-enabled mobile phones for travel survey purposes. One of the experiments compared smartphones and specialized GPS devices to explore the accuracy of the position data obtained by mobile phones. Another experiment studied how keeping the mobile phone GPS online all day might affect the battery life and attempted to seek a proper energy saving strategy for a mobile phone-based household survey application system. The experimental results indicate that the position data obtained by the cellphone-based GPS are comparable to those acquired with a stand-alone GPS device, thus having sufficient accuracy for passive household travel surveys. In addition, the cellphone battery provided sufficient power supply to support the household travel survey for an entire workday when a power-efficiency strategy for GPS usage was implemented. It is therefore feasible to use GPS-enabled mobile phones instead of standalone GPS devices for household travel surveys.

In recent studies, the Probabilistic Principal Component Analysis (PPCA) for imputing missing data was shown to be a good tool for traffic flow data processing. The PPCA method has two major benefits: it results in significantly smaller reconstruction errors and much less computation time, which make it outperform the conventional historical and regression imputing methods. In this paper, the possibility of applying more complex PPCA methods, e.g. Kernel Probabilistic Principal Component Analysis (KPPCA) or Mixed Probabilistic Principal Component Analysis (MPPCA), to impute missing data is explored. Considering reconstruction errors and computation time cost, test results show that the basic PPCA method is still our first choice in missing data imputing for traffic flow for online systems.

Due to the fact that penetration rates of both video detectors and micro-wave detectors are quite low on interrupted flow, it is very hard to effectively estimate link travel time on the whole road network based on these two detector data alone. In order to solve the problem, a data fusion model is being brought forward to estimate link travel time based on video detector data and microwave detector data. In the model, link travel time consists of two parts--travel time without signal delay and signal delay, microwave detector data is used to estimate travel time on the link without signal delay and video detector data is utilized to estimate signal delay at the downstream intersection. In the end, field data from Suzhou is collected to validate the model, and results prove to be satisfactory.

Control delay is a key performance measure for evaluating the level of services of signalized intersections. The existing empirical data-driven methods are difficult to determine the average control delay precisely and efficiently. This paper presents a semi-automatic processing approach to quickly measure average control delay using surveillance video data. On the basis of the vehicle trajectories obtained using video processing techniques, three critical points along the vehicle trajectories are extracted manually: the first two critical points are before the vehicle decelerates to determine the stable driving speed of the vehicle, and the third one is after the vehicle completed the acceleration to resume the stable speed of the vehicle. Using the coordination of these three critical points, the control delay for each individual vehicle can be estimated. The approach is verified in an intersection of Shanghai. The results show that the average control delay can be properly measured with relatively short computation time and low cost.

In intelligent transportation systems (ITS), various detectors - such as the Sydney coordinated adaptive traffic system (SCATS), the global position system (GPS), and the microwave detector - are deployed in the urban road network. Traffic data detected from these detectors are generally heterogeneous. In this paper, the heterogeneous multi-sensor traffic data will be integrated and formally represented to provide a data resource to be effectively shared by various ITS applications. In this framework, the directive road segment is expressed as the basic element, and a three-dimensional spatio-temporal data domain is established to formalize the data representation. In the data domain, the heterogeneous traffic data are transformed to extract the spatio-temporal information as well as the traffic state features - such as speed, flux, and queuing time - therefore constituting a vector as the basic data element of the domain. Moreover, as an attachment to the data domain, a related sparse matrix is constructed to further demonstrate the relations among different directive road segments. As a case, the traffic data detected by SCATS and GPS are respectively transformed into flux of road segments, and the flux of next time is predicted by combining the related sparse matrix and the flux matrix of previous time.

In order to solve the problem that the performance of traditional Automatic Incident Detection (AID) detector was restricted due to the imbalanced training set, a SVDD (Support Vector Domain Description) algorithm was brought in to detect traffic incidents. Using actual traffic data from the America I-880 freeway, the proposed SVDD-AID algorithm was trained and its performance was tested. The experimental results show that the model parameters should be chosen carefully because they have great effects on the classification result, and the SVDD-AID algorithm can obtain desirable detection performance.

The system which is road traffic congestion information independently collecting and dynamic transmitting based on Vehicular Ad hoc Network (VANET) is a novel traffic service mode which faces the road traffic congestion information, and it mainly focuses on road traffic congestion information independently collecting, integrating, processing and dynamic transmitting through the vehicle itself traveling mobility and vehicle information resources. First, on the basis of studying the system mode, a corresponding system model is built. Moreover, the rationality and effect of this model is evaluated and analyzed by traffic simulation system. Furthermore, the simulation results of the system mode and its associated model in automatic collection and dynamic transmission of traffic congestion information show the certain feasibility, and it will be required further studies to the dynamic propagation of information in complex road network.

The bus transit system is required to run in a green manner for impact on the urban atmosphere. This paper explores the possibility of reducing emissions using regional bus scheduling. The optimization model is established based on the integer programming theory. Depot capacity, fuel restrictions, time constraints, and other factors are considered in the model. The target of the model is to minimize the vehicle operational costs and emission damage. The best parking depot and operation schedules of vehicles could be made with the help of the model. According to the features of problem, an improved ant colony algorithm is presented. The variable neighborhood search algorithm is applied for local search for better performance. A network composed of different bus lines is selected for case analysis. The results show that the model can put forward the better scheme, which improves the utilization rate of vehicles and reduces pollution emissions.

Accurate information on turning movements at signalized intersections is a critical requirement for many applications such as adaptive traffic signal control systems. A variety of sensor technologies has been developed for real-time traffic monitoring, such as loop detectors, traffic cameras, and radar. However, most of them are limited to provide link traffic information with few being capable of detecting turning movements. Several attempts have been made in the past to develop algorithms for inferring turning movements at intersections from entry and exit counts; however, the estimation quality of these algorithms varies considerably. This paper introduces a constraint optimization algorithm to estimate turning movements at signalized intersections. The new algorithm makes use of additional movement information available from the status of the signal heads at each phase to minimize estimation ambiguity. A simulation analysis is conducted on a four-leg, two-phase signalized intersection to evaluate the estimation performance of the proposed method. The results show that the algorithm is highly accurate and robust and fairly straightforward for real world implementation.

This paper is concerned with the knowledge mining approach in application to complex transportation systems. The approach is based on implementing the author's original mathematical models and supporting them with risk prediction software technologies. Compared to existing methods, the analytically calculated risks depend on the time of periodic control, monitoring, and recovery. Rational use allows the problem to go from data mining according to events to knowledge mining from transportation safety monitoring data and statistics. On the basis of the mined knowledge, proactive decisions may be found before the occurrence of critical events.

Road traffic accidents have become a major public hazard for all mankind. Therefore, the study of traffic accidents is always an important subject to scholars all over the world. A road safety evaluation is an effective way to identify potential accidents and reduce accident severity. At present, the major methods of foreign traffic safety evaluation include the rate of relative accidents, time series analysis, regression analysis, systems analysis, and traffic conflicts. Based on the analysis of a large number of accident statistics, these methods qualitatively analyze the factors affecting traffic safety and use mathematical theories to establish the quantitative relationships between traffic accidents and various factors, thus reflecting the safety level of the road. Based on the road conditions, traffic safety facilities, and traffic environment, this paper analyzes the factors affecting the road safety and establishes a safety evaluation system for arterial highways. The index-measuring approach is also employed with an analytical hierarchy process, and the theoretical model of evaluation methods is proposed.

In traditional EOQ models, material purchase cost per unit is assumed as a constant and purchase cost is fixed. Just holding cost and ordering cost are considered as variable factors of influencing final total cost. In fact, in many industries, the unit price keeps obvious trend of fluctuation. Especially, in electronic field, price of same material or part normally drops much in a year. Therefore, the traditional EOQ model is not applicable to purchasing of this field. This paper resets equation of total cost based on variable price and takes purchase cost and ordering, cost and holding cost as variables into account to updated EOQ model. Thus, the model will be more applicable to the procurement of electronic industry.

At present, logistics costs of fresh agricultural products are high. The operation and management level of logistics lags far behind that of some developed countries. The concept of logistics safety of fresh agricultural products is addressed at first; then ISM is built to analyze and evaluate the safety risk critical factors related to the logistics of fresh agricultural products sale. The weights of first-level indices are determined by AHP. The risk level of sale logistics for fresh agricultural products is evaluated by the combined fuzzy evaluation method. Finally, this paper indicates the feasibility and validity of this method by Wuhan example. Our country is a large agricultural country, and the demand on the fresh agricultural market is increasing as the agricultural trade, both in and out of the country, continues to grow. However, a large emphasis on production and slight emphasis on circulation have created a severe restriction for the safety and rapid circulation of fresh agricultural products. The phenomenon of disjointed and low circulation efficiency in the fresh agricultural products supply system was largely derived from the lagging development of agricultural products logistics. Nowadays, our country is more concerned with production and machining processes and less concerned with the security issues in the logistics sales process, where the agricultural supply system is held in the storage and transport mode. Lack of main operations coordination, the ineffective supervision of some departments in the process of marketing and distribution of fresh agricultural products, the imperfection of the cold chain system, and the low rate of fresh refrigerated transportation of agricultural products are all issues directly causing severe loss in the fresh agricultural production and circulation process, resulting in frequent accidents from food safety (He, 2006).

To improve the high-risk situation of driving on icy road in cold weather, a more economy applicable measure for road ice forecasting is proposed compared with the Road Weather Information System widely used abroad. A temperature-controlled laboratory with a short section of road was used to simulate the scene driving on the highway. According to the changes of temperature and precipitation, the corresponding changes of temperature close to the surface, road surface temperature and road surface ice were recorded to show the rules of the road surface temperature changes and icing development. The main purpose was to build the road surface ice prediction model. After the network training of the experiment samples using a BP neural network, the road surface ice prediction model is put forward, especially for the ice prediction of some high-risk sections, including bridges, tunnels, shady sections etc. Besides, the method contributes to the development and application of low cost icy road prediction techniques.

Driver's fixation characteristics can express visual information processing course, studying on driver's eye fixation characteristics during freeway tunnels is necessary to evaluate the safety of tunnel environment. By using IViewX HED Laptop system, driver's eye fixation characteristics were taken as research objects, 4 typical long tunnels on the same freeway were selected, 32 times valid experiment were carried out for 8 drivers. The distribution characteristics of eye fixation point were obtained, tunnel stage was divided into 7 stages and comparative analysis of eye fixation characteristics was made by 7 different stages. Whether in daytime or at night, the lower limit of the fixation points range is significantly larger than the minimal safe brake time (0.5s), the barycenter of the eye fixation distribution is lower than the eye horizontal line, the areas of plane distribution range at 7 different stages can be sequenced from big to small as: normal stage after the tunnel exit>normal stage before the tunnel entrance>light adaption stage inside the tunnel >middle stage in the tunnel>light adaption stage (50m's distance before the tunnel exit)>dark adaption stage inside the tunnel >dark adaption stage (50m's distance after the tunnel entrance). The analysis can lead to the conclusion, the visual load during dark adaption stage inside the tunnel is much heavier than light adaption stage, the visual load at tunnel entrance and tunnel exit is much heavier than on the middle stage of the tunnel, which makes drivers more easily miss road information during the tunnel stage. So it is necessary to set up road signs and markings based on the distribution range of driver's eye fixation characteristics in freeway tunnels.

In this paper, a modified version of the existing social force model is proposed to simulate an evacuation procedure in a classroom with different psychological conditions. Based on the numerous studies on the implementation of social force model in modeling evacuation motions, it is notable that most of the published studies do not take into account the pedestrians' psychology in their models. To reflect the effects of different psychological conditions, we develop a modified social force model, incorporating a stop mechanism with variable distance, which is related with the psychological factor of pedestrians. Simulation experiment is presented for validating the proposed model. At the same time, the phenomenon that more anxiety causes more clogging is also observed in the simulation. The improvement in our proposed model is valuable for further study and for upgrading the safety aspects of building designs.

With the constructing and repairing of infrastructure, road work is increasingly common and has a great influence on traffic flow, causing congestion and easily forming traffic bottlenecks. The traffic model of road work zones is concerned by scholars gradually. Flock theory as a bionic model can characterize the characteristics of the traffic flow well. In this paper, a flock obstacle-avoidance model is established with flock theory. The model is calibrated to explain the characteristic of vehicles in road work zones, of practical significance in designing the layout of work zones.

The most important issues in human reliability analysis (HRA) are the analysis of the information gotten from the task, its uncertainty and its treatment while using accurate techniques. This leads to a quantification of the performance shaping factors (PSFs) and then to human reliability quantification. The purpose of this paper is to compare the information required by the classical and the second generation model, especially the unified reliability model, to highlight the importance of cognitive task analysis. This newest approach proves to be more accurate in quantifying human performance by focusing on analyzing both the task cognition and physical demand and the operator resources. The bases for a task analysis in the unified reliability model, its source or collecting method and its uncertainty treatment will be established. Also, the dimensions of the unified task analysis and its relation with human error will be presented.

The behavior of secondary task has an important influence on driving safety. It is necessary to build a precise driving model for accurate analysis of the influence of a secondary task on driving performance. The vehicle preview trajectory curve and steering control strategy are based on two different preliminary aim modes - the far point and the near one. Through the adjustment of a vehicle's acceleration and deceleration according to the distance between the vehicle and the lead vehicle, a controllable method of vehicle running speed is determined, which regards the lead vehicle tail center as its tracking target. Finally, the driving model is built and the experiment shows that the model developed in this study conforms to reality better. Based on the model and the software Distract-R, successful analysis of the effect of secondary task on driving performance is achieved.

Based on the theory of driving stress training and impetus customization, a driver stress training system was designed to reduce traffic accidents because of drivers' lack of stress response ability when driving on the rural road. According to the characters of traffic accidents on rural roads, stress scenes were developed. In the experiment, 30 subjects were selected to attend typical conditions for the virtual simulation rural road driving experiment on the system platform. Heart rate was detected by MP150 simultaneously to indicate any variation of stress response ability. Experimental data was analysed using logarithmic regression and relativity analysis. The model between the stress level of this stress system and the training times was established, and the matching training standard was put forward. The results showed that stress response ability was strengthened with the addition of training times. Trained on different stress driving scenes under urban road condition according to the established training standards, driver was relaxed and response ability was promoted. Demands of stress response were satisfied by the training system and standards established. Stress response ability of drivers can be promoted and these types of traffic accidents can be reduced efficiently.

Road safety affects health and development worldwide, thus it is essential to examine the factors that influence crashes and injuries. As the relationships between crashes, the severity of injuries, and possible risk factors could vary depending on the type of collision, we attempt to develop disaggregated prediction models for different crash types in terms of number of vehicles involved in the crash (i.e., single- and multi-vehicle crashes). As disaggregated speed data are available from the probe vehicles equipped with global positioning system (GPS) devices, it is possible to determine how average speed and its dispersion affect crashes and injries. We also examine risk factors, including geometric design, weather conditions, and temporal distribution. A comprehensive database is thus established with information on road crashes and other possible risk factors for selected road segments in Hong Kong. In particular, a joint probability model is applied to analyze crash occurrence and severity simultaneously under an integrated modeling framework. As a result, speed plays an important role in road safety performance. Furthermore, rainfall and several geometric factors are also significantly associated with crash occurrence or severity.

On the basis of laying weather detectors and tire sectors on the vehicle and traffic detectors along a sharply curved road section, some parameters related to weather and vehicle traveling are collected to calculate the adhesion coefficient and rolling resistance coefficient through artificial neural network. Then, the safe distance between vehicles is obtained, combining with velocity and road design parameters. At the same time, the actual distance between vehicles can be calculated by the velocity and the time traffic detectors recorded when a vehicle is approaching. If the actual distance is less than the safe distance, an alarm device will warn the vehicle to reduce its velocity in order to avoid a rear-end collision in adverse weather conditions.

In this paper, the features of the present traffic safety evaluation methods at signalized intersection at home and abroad are analyzed and the weaknesses of the traditional methods based on accident statistics are revealed. Then, the paper describes a non-accident statistical safety evaluation method, the Traffic Conflict Technique (TCT). Meanwhile, the paper puts forward a safety evaluation method based on Traffic Conflict Technology and gray clustering, which takes three (TC/MPCC) values into consideration, namely that of morning climax, common and evening climax. Finally, the method is applied to five intersections in Beijing as an example and tests the accuracy and feasibility of the model, indicating that it has a better utility value.

Safety has always been an important component in the planning, design, and operation of highways. A framework for highway safety mitigation is outlined in this paper that provides a logical and comprehensive context within which efforts to improve highway safety can be made. This framework incorporates predictive methods of highway safety analysis to allow transportation officials to proactively improve the safety of the transportation system. This framework has been developed around the Roadway Safety Management Process contained in the Highway Safety Manual (HSM) and has six primary steps: 1) Network Screening, 2) Diagnosis, 3) Countermeasure Selection, 4) Economic Appraisal, 5) Project Prioritization, and 6) Effectiveness Evaluation. In addition to methods used in the HSM, alternative methods of predictive highway safety analysis are discussed in context of their application. This framework for safety mitigation can be applicable to transportation agencies worldwide to maximize benefits resulting from highway safety investment.

In order to determine a reasonable maximum speed limit value and luminance at crosswalk at nighttime, it is necessary to study performance of driver distance recognition to a pedestrian crossing at night. An experiment was carried out on six segments in Harbin, China. Based on trips made by eight drivers during the night on these segments, driver recognition distances (distance between a pedestrian and the location where the pedestrian was clearly recognized the first time) were recorded. The data analysis results show that driving speed increases, recognition distance decreases; luminance decreases, recognition distance decreases. With the collected data, multivariate a non-linear regression relation model was established among driver recognition distance at night, driving speed, and average luminance.

Recently, with the increase in traffic accidents, more and more attention has been paid to road safety. Traffic ergonomics is the focus on improving the coordination among people, vehicles, and road environments from the angle of traffic participants based on ergonomics. In this paper, by the theory and method of traffic ergonomics, a variety of factors that affect highway safety were analyzed and summarized to establish a highway safety evaluation system based on traffic ergonomics. The evaluation system contains a level one indicator and four level two indicators, and there is a summary of the contents for each of the level two indicators. Finally, an accident-prone segment of Badaling Expressway was taken for example. There were analyses of reasons for accidents and measures for improvement based on the highway safety evaluation system.

In this paper, the driver's intention recognition on roads without crossings is investigated. Because of uncertain characters between driver's intention and behaviors, analyzing and modeling methods based on the hidden Markov model (HMM) were proposed and used for setting hidden or observed states, obtaining probabilities of intention transition and observation, and building a graphical network of those definitions. In order to meet the dynamic requirement of the state transition, the structure of the HMM is improved to a sectional form, which is named SHMM, with road subsections. The transition probability of alternative intentions is designed as a time-domain continuous function, and the probabilities of observation are counted and made into statistics with the respective distribution in the subsections. The Viterbi algorithm is used for recognizing intention, with sequences of operation in the whole process of driving. The judging rule is drawn up to decide all operations in the sequence they're driven by, i.e. which type of intention with number comparison. The data used for modeling and verifying in this study is collected by a real vehicle driving experimental platform, and the test is held on urban traffic roads with ten participants involved. The results of intention recognition under the proposed method is quite satisfying and credible.

In this paper, a method for vehicle driver's intention recognition is investigated through an optimized hidden Markov model (HMM). As uncertainties exist between modeling and application of intention recognition with HMM, the Baum-Welch (B-W) algorithm is introduced to optimize and update the parameters of the established HMM. The major steps within the optimization process, such as acquisitions of forward probabilities, backward probabilities, maximum expected probabilities ratio, elements updates of matrixes π, A and B, and setups of recursion terminated condition, are fully described in the paper. An elaborate example presented at the end of the paper shows the credibility and effectiveness of the proposed algorithm.

Expressways remain the black spots of sleepiness-related accidents. Evidenced by statistical data, off-ramp, as an inevitable route of expressways, has the highest accident rate. Therefore, security issues related to drowsiness driving on off-ramps appeal to closer attention and further discussion. This paper takes the simulator-based drowsiness driving performance on off-ramp as the study objective, collecting data about vehicles running parameters and 22 drivers' manipulation of vehicles. Data were collected under fully alert as well as drowsy conditions, including speed, lateral position, and steering wheel movements etc. The results show that driving performance on the off-ramp is significantly affected by drowsiness. The conclusion of this experiment will bring a fresh perspective for further research on drowsiness driving under different road conditions.

Understanding how users will respond to new in-vehicle technologies can be a crucial factor in the success of future Intelligent Transportation Systems (ITS) implementations. This study's main goal was to evaluate the social acceptability of different ITS that varied in the control and monitoring levels over vehicle parameters and driver's performance and to describe the most common socio-psychological factors that influence ITS acceptability. We developed a novel ITS acceptability measure, composed by a 51-item questionnaire. The participants had generally high levels of acceptability, independently of the ITS control level over driver's performance. However ITS that exerted more control were regarded as more efficient. We also found gender differences, especially in a "Personal and Social Aims" dimension. Age is positively correlated with participants score on the acceptability index, while education level is showing an opposite tendency. Finally, and critical to ITS development, controlling the car velocity is evaluated as the least preferable ITS feature.

Carbon fiber - glassgrid anti-ice asphalt pavement is always accompanied by heat conduction, convection and radiation in the process of heat generation. The temperature in the upper layer will be lower in freezing weather so that less heat loss is caused by radiation, and the heat conduction and convection may mainly affect the temperature distribution in road structure layers. The paper built a pavement finite element model for carbon fiber - glass fiber grille anti-ice asphalt pavement by ANSYS, determined the temperature field boundary and initial conditions, calculated and determined the input power under different ambient temperatures, wind speeds, ice thicknesses and analyzed the ice-melting time.

Considering driving speed and merging angle, the measure of traffic conflict was proposed based on the characteristics of merging behavior in a freeway work zone. The calculation model of driving risk value was established in a merging area of a freeway work zone. The vertical component of the driving speed was used to describe the driving risk value in merging area of freeway work zone. Based on the traffic conflicts risk criterion and test data, the traffic conflicts level was defined in the merging area of freeway work zone. The results of this study show that the driving risk value of dangerous, moderate, and security states are (≏, 5), (3.55,5] and (0,3.55], respectively, in the merging area of a freeway work zone.

This research tries to recognize all primary factors that are associated with speed variation on multilane highways, including roadway access density, which is considered to be the most distinct contributing factor. Additionally, other factors are considered for this purpose: configuration of speed limits, characteristics of traffic volume, geometrics of roadways, driver behavior, environmental factors, etc. A microscopic traffic simulation method based on TSIS (Traffic Software Integrated System) is used to exploit mathematical models to quantify the influences of all possible factors on speed variation. It was found that SSD (Speed Standard Deviation) of roadway segment increase with the increase of access density, traffic volume and speed limit. Adversely, SSD decrease with the increase in the number of lanes. It is concluded that new access density can represent a number of characteristics of access point, which could directly affect the roadway safety; such as access density, traffic volume of main road, number of lanes of main road and speed limit; a statistical model is proposed to show that access density, traffic volume, and speed limit have positive effects on SSD, while the number of lanes has negative effect.

This paper demonstrates how the distribution of superelevation and side friction factors over a range of curve radius changes in designing a SMART highway that will be a new design higher-speed 140 km/h highway. The brainwave test and a field study of vehicle speed were carried out in the research to determine proper rates of superelevation and corresponding side friction factors on such high-speed highways. The brainwave test result showed that adjusted side friction factors over a range of curve radius should be applied in SMART highway design. This is due to the driver's changed behaviors on high-speed designed highways, in particular their cautious speed behaviors and sensitive perception of side friction forces. Traditionally, highway engineers applied the Ball-Bank indicator to capture drivers' feelings of discomfort on highway curves, but this research demonstrated that the brainwave test would be a better alternative.

There are many factors contributing to traffic collisions and their severity. Different major factors are likely to contribute to traffic collisions and their severity for different groups of people. Clearly identifying the major contributing factors to traffic collisions and their severity for different groups of people will assist highway safety improvement initiatives by improved facility design and educational program to address the needs due to the changes in demographics. The traffic collision data used in this study has been collected over the last 20 years on the rural highways and urban streets from Saskatchewan, Canada. In order to determine the major factors contributing to traffic collisions and their severity for different groups of people, we present a data mining model using ID3 and C4.5 decision tree algorithms to analyze the traffic collision data in this paper. The experiment results from this study will show that the developed data mining model using decision tree can effectively classify the major contributing factors to traffic collisions and their collision severity for different groups of people with good accuracy. The major contributing factors to traffic collisions and their severity for different groups of people are compared.

Mountainous freeways are a serious road hazard which is generally associated with high crash rates and serious human injuries. This study aimed to investigate the safety effects of various relevant risk factors associated with mountainous freeways by developing crash frequency prediction model. The data of analysis were obtained from a 20-mile-long mountainous section on Colorado Interstate-70, which is regarded as one of the most dangerous roads in the United States. As over-dispersion and zero-inflation problems were observed from the subject data, a zero-inflated negative binomial model was established. Estimation of the model coefficients indicates that features such as steep slopes, curves, seasonal factors, and tunnels significantly contribute to crash occurrence on mountainous freeways. The relative effect of each risk factor was also calculated to evaluate the relative significance to road safety. Notably, a new method was proposed to evaluate the relative significance of the variables under the zero-accident state. The research results from this study are helpful in crash hotspot identification and safety countermeasure development.

Traditional driving behavior researches mainly focus on the identification of drivers' bad driving behaviors. However, the traditional method is hardly competent for quantitatively measuring the degree of driving behaviors' risks, and it is not qualified for supporting value-added services based on the assessment of driving behaviors, such as vehicle insurance service. Through analysis of the vehicle travel state information such as steering wheel angle signal, brake pedal signal, and so forth, which are collected by the multi-sensor equipped on vehicles, this paper established a correlation method between vehicle status information and driver's different driving behaviors. Furthermore, this paper proposed a driving behavior tendency degree measure method based on vehicle status information by means of multi-index Analytic Hierarchy Process (AHP) and fulfills the construction of the fusion decision model about the degree of the driving behaviors by means of BP neural network. Finally, the outputs are mapped to a radar chart which enables the risk degree of different driving behaviors to be presented straightforwardly. Verified by driving data, the method provides a better comprehensive assessment of the risk of driving behaviors.

Traffic accident morphological analysis is the prerequisite and condition of accident warning. Grey Relational Analysis is one of the important methods of morphological analysis of the accident, which can effectively solve the problem of inadequate sample size defects but cannot solve discrete data caused by the results of the analysis of the distortion problem. This paper adopts the least square method to improve the analysis of the correlation degree. The results show that the new method can effectively improve the accuracy and precision of the analysis, which provides a new means for the accident morphological analysis.

The expressways in China have made great achievements and have played an increasingly important role in the economic development. The purpose of this paper is to analyze the traffic safety characteristics of expressways in China and to provide the basis for the targeted countermeasures to improve the expressways' traffic safety. The trend of the accidents on expressways in China is analyzed using the time series analysis method. The safety situation and the characteristics of the accidents on expressways are analyzed. Although the fatalities of the accidents and the proportion are high, the safety advantage of expressways is obvious compared with the other highways. The prominent problems of the accidents on the expressways include rear-end collisions, scraping against pedestrians, speeding, fatigue driving, and devastating accidents with over ten fatalities in one accident. As a result, measures should be taken to solve these problems.

Signalized intersections are provided in traffic networks to improve the safety and efficiency of vehicular and pedestrian movements. However, the trade-off between these two items is always a big issue. Most existing methods evaluate the operation of intersections from the view of safety or efficiency separately, and many of them evaluate the level of service of each transport mode individually, often neglecting bicycles and pedestrians. An objective evaluation methodology is needed to comprehensively evaluate both the efficiency and safety of all road users simultaneously. Thus, a new evaluation method is proposed by this paper. Based on the definition of multimodal level of service (MLOS) (delay related) and multimodal safety level of service (MSLOS) (conflict related), a comprehensive performance index, the multimodal comprehensive level of service (MCLOS), is established. With the VISSIM-SSAM simulation platform, a case study of a typical intersection underlines the strengths of the assessment method.

This paper studies the design method for the dynamic scale model of a pedestrian footbridge. A typical pedestrian footbridge was taken as the prototype. The actual structural properties and dynamic mechanics theoretical analysis based on the dynamic similarity theory for the scaled test model was used so as to deduce structurally similar ratio parameters in the scale model. Then, combined with the practical feasibility, the model is designed and produced. Compared with the dynamic field test, the finite element method analysis shows that the dynamic properties of the scaled model are very similar to the actual prototype. This designed scale model can satisfy the study on the dynamic response of pedestrian footbridges under pedestrian loads or ambient excitation. This design method for the dynamic scale model of pedestrian footbridges supplies a new approach for the study on vibration serviceability of pedestrian footbridges.

Currently, the prevention of devastating accidents is still the focus of accident prevention in China. Despite the serious consequences and the huge impacts, the complete elimination of the devastating accidents is unrealistic due to contingencies. Moreover, the number of devastating accidents is relatively small and the proportion is very low. Fatal accidents, including devastating accidents, should be the focus of the prevention. However, due to lack of the macroscopic analysis and research, the guidance for the prevention of fatal accidents is missing. Fatal accidents in China are analyzed with the time series. Characteristics of fatal accidents in 2011 are analyzed based on the statistics, and measures and policy recommendations are put forward. Curbing all fatal accidents, including devastating accidents, should be the most important goal of road traffic safety. The macroscopic analysis, accident information collection of the fatal accidents, and the in-depth analysis of the fatal accident cases should be strengthened to further curb fatal accidents.

When driving on the highway, the bus drivers' level of safety consciousness was low and this was the root cause of some serious and major accidents. The level of safety consciousness came from drivers' hearts, so to measure and study was difficult. To measure objectively the level of bus drivers' safety consciousness, a certain sample of bus drivers was selected as research subjects by using an objective evaluation method to calibrate the level of safety consciousness. The number of accidents, driving speed, speed dispersion and the maximum value of speed were taken as alternative evaluation indicators, and correlation relationships between various indicators and the level of safety consciousness was studied. Then the computation model of the level of bus drivers' safety consciousness was established. The result indicated that the level of drivers' safety consciousness was related to the number of accidents and speed dispersion. It was not related to the mean value of speed. It was strongly related to the maximum value of speed. It could evaluate the level of drivers' safety consciousness by using the maximum value of speed during the statistical period, then classify according to the relevant fuzzy discrimination model. Examples show that the evaluation model based on the maximum value of speed is effective.

The Yangtze is the most important shipping waterway in China. As such, the safety assessment of navigation in the Yangtze River is very important to the development of China's shipping. The current evaluation model pays more attention to the influence of a single navigation risk factor, ignoring the interaction between risk factors. This paper introduces system dynamics to analyze of risk factors that affect the security of the Yangtze River shipping industry. The study found that the level of professional skill of the crew is the biggest risk factor. In order to reduce the risk of Yangtze River shipping, it is suggested that shipping companies strengthen crew management and enhance the professional skills of the crew members.

With the popularization of drop and pull transport's organization mode, more and more combination vehicles will be on highways in China. There are many accidents caused by trucks. Drop and pull transport demands higher speed and better reliability for vehicles than before. This paper analyzed the key factors influencing transportation process and put forward to use Analytical Hierarchy Process (AHP) to evaluate the safety of cargo's transportation on road. The experts rate the relative importance between factors in basic index layer and criterion layer, and then the weight of all factors in criterion layer to target layer can be calculated. The results showed that supervisors can evaluate the safety of loaded trailers according to the detailed information of transportation. Finally, this paper brought forward checking rules for different stages of cargo loading and transportation.

The oil transport enterprise has a significant effect on national energy security and economic development in current conditions. In the background of economic transition, the industry is facing crisis and the development facing adjustment - strengthening oil transport enterprise security management is very important. Therefore, according to the characteristics of oil transport enterprises, we established a safety evaluation index system of the oil transport enterprises from four aspects: management, technical, social, and environmental. In accordance with the relationship between the index of the interaction, we constructed the network structure of index system. Then a security evaluation model of the oil transport enterprise based on F-ANP was established, at last showing the feasibility of the model through examples. The model provided a scientific and reasonable method for oil transport enterprise running safety evaluation, had better practical value and significance for the oil enterprise production safety management.

The mountainous area composes approximately 2/3 of our whole nation, so the mountain road safety situation is grim. The paper starts from the characteristic of mountain road accidents. There are higher death rates and more major traffic accidents. In the major accidents, more fall to the roadside and the vehicles are complex. By the actual survey in Sichuan Chongqing Yunnan and Guizhou, the mountain road safety facilities are checked. The characteristics and problems are found. Through the road traffic accidents analysis and the existing status of mountain safety facilities, the mountain road safety technology policies are given, which will provide a reference for managers.

Driver's emotions are one of the core factors that affect the running characters of vehicle which also impacts the traffic safety. Moreover, of all the driver's emotions, angry driving is the most evident. However, in general, angry driving is rarely considered into traditional car-following models. In this paper, an improved car-following model that considers angry driving is proposed. First, the theory of Weibull distribution is used to calibrate the definite desired time headway whose scope were already acquired from ten groups of on-road experiments to reflect the drivers' emotions. Then, the fuzzy inference was adopted to establish the new car-following model because of its indetermination and fuzzy characteristics of the driving process such as drivers' subjective judgments, reasoning and decision making. Finally, the new model under special scenery has been simulated in Matlab/Simulink. The simulation results indicate that (1) the angrier the following driver is, increases the rate of acceleration or deceleration the following car moves at, which means the driver adopts more excessive range of vehicle operation, (2) The relative distance away from the front car is larger when the following car decelerates while smaller when accelerates under angry driving than that of normal driving.

With the industrial development in China, more and more dangerous chemicals are transported via roads; so, the transportation of dangerous chemicals is thriving. However, due to a late start in the development of this form of transportation and many existing problems, a large number of accidents occur when transporting dangerous chemicals. The author analyzes reasons for those accidents, including low quality of practices, terrible vehicles and facilities, management defects, poor road traffic conditions and bad natural conditions. The author also proposes corresponding development countermeasures to effectively reduce or even avoid the accidents.

Based on the velocity effect (VE) model, a cellular automaton (CA) model is proposed with the consideration of timid and aggressive driving behaviors. Numerical simulations are performed to investigate the characteristics of traffic flow. The flux-density curves are plotted. The results show that the maximum flux and the corresponding density decrease as the proportion of timid drivers increases, while they increase as the proportion of aggressive drivers increases. In addition, road capacity is also investigated with the consideration of various driving behaviors. The results show that only a smaller proportion of timid drivers can play an essential role on the road capacity, while it needs much more aggressive drivers to promote the road capacity.

Driving errors may result from high workload caused by traffic signs with too much information; it could result in traffic crash significantly. Therefore, the information volume of traffic signs must keep to a reasonable level to be recognized well. In order to make drivers recognize traffic signs, the information volume that the driver could endure in different workload levels should be known clearly. In this study, we designed and implemented experiments to analyze drivers' recognition time and workload on different traffic signs information volume. The probe Shannon Theory was adopted to measure the information volume of traffic signs; the participants are required to search the target road name from traffic signs with different information. The Reaction Time (RT) would be compared with the available visual recognition time under real driving scene conditions. If the RT was almost equal to the available visual recognition time, the information volume included in the sign was considered to be the maximum information of the sign under this situation. Subjective difficulty questionnaire was used in the experiment to value driving workload. Results indicate that the information of traffic signs will increase driving workload; the maximum information in different driving speeds is also gained through the experiment. The results contribute to a better understanding of the information volume of traffic signs in different driving speed, it also has positive effects on traffic sign design.

Angry driving has become a serious social problem affecting traffic safety. The vehicle speed under angry driving is different from that of normal driving. However, the characteristic of vehicle speed under angry driving is not clear. To elucidate the mechanism of vehicle speed, nine participants were recruited to carry out an experiment using a driving simulator. The results show that the means, standard deviations, maximums, and ranges of vehicle speed in anger driving are significantly greater than those in normal driving, respectively. Independent samples to test for equality of means verify that the mean of vehicle speed in anger driving is unequal to it in normal driving. The maximums of amplitude in a three-dimensional, time-frequency-amplitude system for vehicle speed were extracted. The time-frequency features of vehicle speed reveal that the maximums of amplitude in angry driving are significantly greater than that in normal driving.

Accidents usually occur at bus stations, especially during peak hours. In China, there are usually more than 30 persons waiting for buses at the same time, and they often stand on the roadway instead of in the waiting area. This study attempts to determine the parking patterns of bus drivers when they are pulling into bus stations. The travelers' behavior at bus stations when they are waiting for buses is recorded by a videotape recorder. It is assumed that the parking position of buses is influenced by the security level of the bus stations. So, experiments were carried out on 10 groups and got 116 samples about harbor-shaped and non-harbor-shaped bus stations. According to the results, it was found that the travelers' waiting habits and cars parking in the bus station area are the main reasons for passenger-vehicle conflicts. However, the bus parking positions are not correlated with conflicts, which is the opposite of what was expected.

In recent years, International Maritime Organization (IMO) and the classification societies have issued a number of regulations and guidelines addressing both environmental performance and human safety of ships. All of these regulations and guidelines are aimed at building improved vessels, but environmental performance and human safety are usually considered separately. Sometimes, this results in the two issues conflicting with each other: a regulation that is intended to improve environmental performance may have negative effects on human safety and vice versa. The objective of this paper is to investigate the conflict and points towards the need for an integrated evaluation of both environmental performance and human safety of ships. As a basis, this paper provides several examples in which environmental performance and safety contradicts each other. Based on the examples, a conceptual description of the problem is provided, including suggestions for further work.

Although all types of road users are at risk of being injured or killed in a road traffic crash, there are notable differences in fatality rates between different road user groups. The "vulnerable" road users (VRUs), such as pedestrians and two-wheeler users, are at greater risk than vehicle occupants. In particular, with the popular use of the electric bicycle, the vulnerable road users involved in traffic accidents (VRUITAs) become more frequent in China. Therefore, the characteristics of VRUITAs were first explored from accident data. The crash composition and other measurements were analyzed in this study. The reasons for VRUITAs in China were then compared with those in developed countries from the aspects of legislation, driving training and traffic management. The results indicate that the vulnerable road users in China were more likely to break the traffic rules and take risky behavior. Several counter measures derived from developed countries were finally discussed to be further applied in China to reduce the VRUITAs.

Drivers may be influenced by some factors, such as the front vehicle's velocity and headway; but, the influences of vehicle honk on traffic flow and driver behavior have seldom been investigated. The present study took this issue into account by proposing a new symmetric two-lane cellular automaton model. It is based on the symmetric two-lane cellular automata (STCA) model that was proposed by Chowdhury. The lane-changing rules of STCA were revised, and some other rules were added that took the honk effect into account. This study also focused on the relationship between drivers' characteristic and honk actions. The results showed that different kinds of drivers made different decisions when their front vehicle hindered him. Based on the observation, the added cellular automaton rules included not only the honk rules but also the driver's characteristics. Finally, some simulations were made. The results showed that the honk action enhanced the flux in the intermediate-density range. Besides, the relation between the percentage of three type of driver and traffic flux was considered. The results figured out that the rash driver's honk increased the lane changing times, which only resulted in the fluctuation of traffic flows. So with the increasing of rash driver's percentage, the traffic flow flux did not increase in the high-density range. As far as the percentage of cautious driver, the traffic flow had less fluctuation than the former results. In summary, it can be argued that the honk behavior is not encouraged in the asymmetric two-lane model.

Due to the lack of a standard knowledge base for scenario sharing in driving simulation community and a standard data source for a new scenario control framework, Ontology for Scenario Orchestration (OSO) is developed. OSO is focused on driving context and scenario tasks, i.e., tasks that should be performed to generate intentional interactions with the participant or simulator driver. This formal description will be passed to virtual drivers who can use the relevant driving context to generate interactions that are embedded into autonomous traffic flow. As a component of a new framework for scenario control in driving simulation - SOAV (Scenario Orchestration with Autonomous simulated Vehicles), OSO has been used in two experiments with human participants based on the desktop version of UoLDS (University of Leeds Driving Simulator). A further test with VTI¹'s driving simulation software is being prepared.

Considering the lithium ion battery, this paper analyzes the influential factors of the SOC and the lithium battery model. Two lithium, ion-powered battery models are proposed. One is the battery-equivalent circuit model (the Thevenin model) and the other is the external characteristic of equivalent model (the algebra model). Kalman filtering is used to estimate the SOC of the battery and is described in detail. The simulation results show that if the error of the SOC initial value is large, the Kalman filter adjusts the SOC value to converge close to the true value. This proves that Kalman filtering is an effective method.

The hardware-in-the-loop (HIL) test rig was designed for the study and development of a vehicle stability control system based on the veDYNA software platform and xPC Target technology. The real-time vehicle dynamics model was established and verified by experimental data, and the vehicle stability control algorithm based on slip was designed and embedded in the vehicle real-time dynamic model. By using the hardware-in-the-loop test rig, the steering wheel incremental trapezoid input test was performed under high adhesion, and the steering wheel sinusoidal input test was performed under low adhesion. The results show that the developed hardware-in-the-loop test rig meets the requirements of simulation and the designed control algorithm can improve vehicle handling and stability effectively.

Considering pure electric mini-buses, a vehicle control system is constructed using a driving layer and an intelligent control layer. After the work modes are analyzed for the pure electric vehicle, the vehicle control strategy is studied, consisting of the pedal signal processing module, failure processing modules, and torque fuzzy logic control module. A road experiment shows that a maximum speed of 102 km/h can be reached, and the travel distance per full charge is 154 km (60 km/h @ speed). This study proves that the control strategy is effective.

Accident reconstruction, data analysis and computer simulation are important means of research regarding pedestrian safety and protection. Pedestrian movement mechanism has a great significance on revealing people-car traffic accident characteristics. Based on a real case, this article applied MADYMO simulation analysis to discuss the pedestrian movement mechanism in real traffic accidents and it relied on the real traffic accident data as a verification tool.

In order to analyze the relationship of eroding influence on semi-rigid barriers, this research mainly used UG to build a model, and VPG and LS-DYNA to simulate analysis reprocessing. From the collision safety simulation analysis of different eroding levels, we determined the relationship between the thickness of the eroded semi-rigid barrier and the collision safety. It will provide powerful theoretical support to improve protective measures of eroded semi-rigid barriers.

Combined with the driving resistance setting of a heavy-duty vehicle chassis dynamometer, the transportation coach coast down test method has already been analyzed by dynamics theory, according to GB/T 27840-2011. Meanwhile, the rolling resistance coefficient and air resistance coefficient have also been obtained by the reverse solving method to the driving resistance, which is completed with the least square method. The fuel consumption ratio of the laboratory virtual condition, which is basis of the engine all working characteristics, chassis dynamometer simulation condition, which is based of C-WTVC condition, real road condition, which is based on top-grade constant speed running condition, have all been researched respectively, which also provides significant advices for overcoming existing problems of fuel consumption of heavy-duty commercial vehicles and for subsequent revising of the GB/T 27840-2011 standard.

In this paper, the crashworthiness of the Taiwan PVC barrier was researched using the method of computer simulation according to the domestic evaluation standard. First, from the perspective of comparative analysis, the simulation experiment schemes were determined primarily based on crash test conditions and test factors of the barrier. Secondly, the "vehicle-barrier" model of each group was set up based on virtual proving ground (VPG) pretreatment software, and the safety of impact between vehicle and barrier were studied from the aspects of the moving locus of vehicle, the acceleration of the vehicle, and the maximum lateral displacement of barrier, etc. The analysis results show that the oriented capability of the PVC barrier and the strength provided by the beam were poor and could not resist a collision with a vehicle. Furthermore, the evaluation factor itself could not meet the acceptance criteria. Thus, further research on the material properties and the optimization of the cross section shape of the barrier beam are of great importance.

Accurately recognizing the road adhesion conditions plays a key role in Anti-lock Brake Systems (ABS). The ABS control logic is built based on the threshold value method. The pressure holding time has been proven to recognize whether the tire is on a high or low friction road in the initial stage of ABS activation. Nevertheless, the accuracy depends on the calculation frequency of wheel acceleration derived from the wheel speed. The combined parameters of wheel acceleration and the step number of step pressurization are used to recognize the joint road from low to high friction. Both the wheel slip rate and the wheel acceleration are used to recognize the joint road from high to low friction. The simulation results validate that the recognition methods are effective.

The vehicle dynamics model is established by the vehicle systems dynamics theory and force analysis of the classic single-track vehicle model. The force analysis takes into account lateral motion, yawing movement, and rolling motion of vehicle. The vehicle turning characteristic is analysis with different steering angles and velocities input. A vehicle travelling in different velocities and radius of curvature roads is studied in a dynamic simulation. Vehicle directional stability and response quality is researched through vehicle system parameters changes, and vehicle driving stability is judged according to the changes of lateral acceleration. Simulation results can guide vehicles under the premise of safety cornering to maintain a certain velocity, and it can provide vehicles safety when traveling with some reference and technical support. It laid the foundation for vehicle roads adaptability research.

The driver's unsafe acceleration behaviors from coach buses, such as hard acceleration and deceleration, are the significant factors that influence passengers comfort and may cause accidents. It is necessary to explain the relationship between passengers comfort and acceleration behaviors. The field experiment with 35 passengers and three professional bus drivers was conducted to determine whether bus passengers comfort is influenced by driving behaviors. Subjective comfort feelings of passengers were collected by the means of questionnaires. The questionnaires were distributed on board and acceleration and deceleration values of the bus were received from CAN bus. Therefore, the subject views of the passengers could be compared to object acceleration data. Finally, the effect of acceleration threshold for passenger comfort on the bus was found. The results show that the passergers start to feel uncomfortable when the acceleration, a is greater than or equal to 1.5 m/s² and the deceleration is less than or equal to -0.75m/s². Therefore driver acceleration skills should be trained before driving buses.

It is necessary to conduct a large number of road tests to evaluate the system performance in the process of vehicle active safety system development; however, the tests are always burdensome, dangerous, and low reproducible. So, a low cost vehicle video and CAN-Bus data synchronous acquisition system is proposed in this paper to solve the problem. The system has the ability to synchronously receive video signals, radar signals, and CAN-Bus signals. In addition, the corresponding software is developed for processing, display, saving and synchronously replaying a variety of signals. Therefore, it is possible to realize reconstruction of the test scenarios, which would help the testers to analyze the performance of vehicle active safety system offline and greatly lessen the workload of complicated road tests.

The multi-sensor-based collision warning system can perceive more information (like vehicle motion status, driver intention, and road traffic environment) than a unilateral system. Thus, it can provide more accurate judgments of driving safety. In this paper, physical and logical framework of a collision warning system based on multi-sensor is designed in detail. Vehicle-to-vehicle communication (V2V), vehicle-to-infrastructure communication (V2I), and vehicular sensors are used to acquire the motion status of the subject vehicle, neighboring vehicles, and pedestrians. Then, the short-term future motion status is predicted based on the Kalman algorithm, and the vehicle collision risk can be detected in advance by a collision detection algorithm. Furthermore, the safe distance threshold as a collision risk indicator is calculated and compared with the predicted distance. Finally, the vehicle collision risk can be detected according to the comparison. Simulation results show that the method is effective for judging the collision risk and providing an accurate warning prompt.

This paper proposes a new test method on a model-based testing of lane departure warning system (LDWS), including model development, virtual integration and test management. Simulated models - like vehicle dynamics, vehicle maneuvers and virtual environment - are developed in TESIS DYNAWare. During virtual integration, the LDWS camera is located in the front of a computer monitor displaying virtual environment to capture pictures of lane marking. Vehicle dynamic model and maneuver model run on a NI real-time platform, which represents a virtual vehicle, and communicates with LDWS controller via CAN bus. Test management can be used in process monitoring, data collecting etc. The model-based method will make it easier to create various test scenarios, which can save time and costs by transferring complex test catalogues to the laboratory. The dangers presented in experiments in some critical scenarios can also be prevented. The repeatable model-based method makes it more convenient to locate the problems, which in return makes it easier to compare and assess systems of different companies objectively.

How to ensure the stability of bundled goods in the process of road transport is a significant issue. In order to solve this problem, we developed a vibration monitoring system in transport based on CAN bus. The system applies MC9S08DZ as system controller and the digital axial acceleration sensor MMA7745 is used as a collector. Then we can ensure the stability of vehicle cargo in extreme working conditions. In addition, the system formulated a special CAN bus application layer protocol for the communication between MCU and computer. The digital acceleration sensor, microcontroller, CAN bus communication module and software module are introduced in this paper. The functions of a vibration monitoring system, such as measurement and communication, are tested by experiment. The experimental data shows that the detection system can be used for automotive vibration monitoring when we deliver goods.

Battery energy safety and reasonable utilization are the kernel problems in the study of electric vehicles. This paper presents a battery energy management model based on the fuzzy control which fuses the driver intentions, battery power, and other information and then realizes the control of driving motor torque output. The real vehicle running tests indicate it can effectively improve vehicle dynamic performance and increase the driving range, compared with the battery energy management strategy that is based on the mileage, the maximum speed, or acceleration control. The battery pack is the only energy source of Electric Vehicle (EV). It will consume the supplement energy for a long time if the battery is depleted. The ability of batteries with different State Of Charge (SOC) to output power is different. The battery SOC is an important factor affecting the performance of EV. In the case of lower SOC, the motor high power output may appear to lack battery-powered cutting phenomenon. In the EV driving process, drivers' driving style, and driving action choice depend not only on traffic and road conditions, but also are influenced by factors (such as the battery SOC) from the perspective of safety and reasonable utilization of battery energy. The battery energy management should not only provide necessary and scientific guidance at any time, but also the largest degree to meet the expectations of driving according to the drivers' driving intention (such as accelerating requirement) in the battery energy control. Drive motor is the battery energy hub. By controlling the drive motor, we can achieve control over battery power. Previous research is based on endurance ability (Giuliano, et al., 2012), the highest speed (Huang 2010) or acceleration control (Lujano, et. al., 2012) of battery energy management strategy. However, the robustness of these single control method cannot be guaranteed. Fuzzy control methods do not require a very precise mathematical model. It has good adaptability, robustness, and fault tolerance advantages. It also has good adaptability to the complex, nonlinear uncertainty of the system. Therefore, this paper will carry out the battery energy fuzzy control method.

Vehicle motion parameters are important detection indicators of distracted driving. However, vehicle motion parameters are rarely used by previous studies and attempts on detection of distracted driving. In this study, the differences of vehicle motion parameters between distracted driving and normal driving are analyzed. In this study, we use the three-axis accelerometer and gyroscope of a device to record and analyze lateral acceleration of vehicle. On-road experiment was conducted to collect testing data. The results show that lateral acceleration change of the vehicle motion parameters have pattern differences between distracted driving and normal driving. It was found that vehicle motion parameters of distracted driving did not obey normal distribution. Suddenly maneuvers of lateral acceleration change under distracted driving, respectively, reaching more than 0.25G (approximately 2.5m/s²). This finding lays the foundation for detection of distracted driving.

Potential impacts of the Adaptive Cruise Control (ACC) system on safety and traffic operation of two-lane/two-way highways have not been adequately researched. This mainly regards how ACC influences the overtaking maneuver when vehicles are equipped with an activated ACC. ACC is intended to keep safe headways between vehicles in the traffic stream; however, this can also affect the overtaking decision and the passing process due to larger initial headways between overtaking and overtaken vehicles at the beginning of the maneuver. In this paper, microscopic simulation model is used to investigate the potential impacts of ACC system on overtaking maneuvers for two-lane highways and its resultant safety and traffic effects. Traffic and safety measures - including average travel speed, percentage of time spent following, number of overtakes, overtaking time, and time to collision with oncoming vehicle(s) - are measured for different ACC scenarios, as well as for normal following conditions where no ACC is in effect. The results showed that ACC can significantly impact safety and traffic indices associated with overtaking maneuver on two-lane, two-way highways.

Both vehicle speed and road geometry are necessary in determining the vehicle's risky behavior. The traditional ACC vehicle regulates the speed considering instantaneous effects of road conditions, but ignoring the geometrical features of oncoming road and accompanied influence on the vehicle dynamics. So, vehicle accidents are likely to happen on these roads. To elaborate on a vehicle's speed on variable road geometry, the vehicle model is analyzed considering road geometry and whether the vehicle can regulate the speed fitting in with the variable road geometry to ensure the ride safety and comfort. Hence, we developed an intelligent speed adaption controller by using Terminal Sliding Mode Control method, which has a fast convergence and good tracking performance. The simulation results demonstrate the effectiveness and stability of the designed controller. The proposed approach can deal well with a combination of adaptive cruise control and intelligent speed adaption on variable road geometry.

To analyze the effect of crosswind on the handling stability of tractor semi-trailers in double-lane change situations, the tractor semi-trailer model and the relative aerodynamic coefficient model were built by using TruckSim. Considering the factors of different crosswind directions, crosswind speed, and vehicle speed, we analyzed the relationship between these factors and the handling stability of tractor semi-trailers in double-lane change situations. The results show that a trailer has movement delay and worse handling stability compared to a tractor. The tractor/semi-trailer is unstable when the vehicle speed is 75 km/h and the crosswind speed is 40km/h or 60km/h. The tractor semi-trailer is stable when the vehicle speed is 70 km/h and the crosswind speed is less than 60km/h.

To analyze the influence of trailer length on the passing ability of a double semi-trailer road train (B-Train), we built a B-Train model by using TruckSim, and confirmed the limit of the steering wheel angle when all wheels of the B-Train moved forward and the turning radius was minimum simultaneously by choosing dry pavement. Then, the turning process was simulated to analyze the relationship between the trailer length and the turning channel width at low speed. The results showed that increasing trailer length leads to the increase of the turning channel width of B-Train; the turning channel width is larger when the length of the first trailer is increased independently than that when the length of the second trailer is increased independently. In addition, according to the simulation results, we built the relation model between trailer length variation and turning channel width using the least-square theory.

In this paper, a multi-sensor integrated intelligent micro-vehicle is designed to evaluate the cooperative platoon maneuvers of IVHS. Considering the tremendous cost in time and money, as well as the risk a real vehicle experiment may involve, software simulation is often used to verify the effect of the control strategy. There are certain drawbacks of this method. For example, it relies on the accurate dynamic model. However, the use of micro-vehicles can solve this problem since it has dynamic features similar to that of real vehicles. With on-board sensors like the encoder module, the ultrasonic ranging module and the digital camera, the running state of the vehicle can be easily collected and sent to the monitoring terminal through radio communication to show the performance of the control algorithm intuitively. Therefore, we can focus on the realization of platoon control strategy.

Steering maneuvers determine the lateral stability of a running vehicle and are considered an important indication of driving performance. To effectively measure the steering wheel angle, we propose an estimation approach by using a built-in smartphone tri-axis gyroscope. First, coordinate transition was applied to the angle velocity about the Z-axis of the phone to calculate the vehicle yaw rate. A linear regression method was then used for the modeling of correlations between the resulting yaw rate and the steering angle. Comprehensive experiments show that the steering angle can be well approximated through the angle velocity when the angle remains within a specified range. In addition, sudden changes of angle can be viewed as occurrences of abnormal driving behaviors. This study shows that off-the-shelf sensor technologies provide a cheap and portable solution for driving behavior monitoring.

Traffic accidents and vehicle safety problems were more and more severe with the sustained growth of automotive production. A telematics service system is presented in this paper for the improvement of vehicle safety. The vehicle operating parameters were monitored continuously by the vehicular data acquisition module, which communicated with the remote service center using the 3G network. Drivers were alarmed when the invisible faults were detected or the maintenance was periodically needed. After a serious collision, the rescue time would be minimized using the accurate positioning on the GIS map. The prototype of the system was implemented and the basic functions were successfully verified by the experiment. In addition, the telematics service system not only improved the vehicle safety, but also enhanced the quality of aftersales service by expanding the system.

Considering the inherent energy-constrained characteristics of the electric vehicle, inaccurate estimates of the state of the charge may lead to electric taxis breaking down on the way. Therefore, the path planning for electric taxis needs to consider the state of the charge. While considering the passengers' time demand and drivers' energy demand, it needs to ensure multiple objects optimization, including the running time, energy consumption, etc. The proposed method designs a multi-objective path planning method with energy-constrained, which converts the energy-constrained path planning to a traditional one by constructing the energy reachable graph. Then, a cost evaluation function is defined by the linear weighted method to solve the multi-objective optimization problem. Finally, a two-stage shortest path method is proposed to deal with the multi-objective path planning problem. The research results show that the proposed method provides a charging recommendation under the energy constraint and effectively reduces the time and energy costs of electric taxis.

Dedicated short range communication (DSRC) technology is one of the basic technologies of intelligent transportation system (ITS). It can provide high speed data transmission, as well as ensure low latency of communication link and system reliability. It's devoted to vehicle short range wireless communication to establish a two-way information transmission between vehicle-to-road and vehicle-to-vehicle. This paper (1) elaborates on the structure and technical features of DSRC protocol; (2) analyzes several existing DSRC protocol standards; and (3) cites the instances of the application of these standards as well, which will provide a reference for the formulation of DSRC standard of our country.

The pavement classification number (PCN) is an International Civil Aviation Organization (ICAO) standard used in combination with the aircraft classification number (ACN) to indicate the strength of a runway, taxiway or airport ramp. This paper introduces a method to obtain the PCN of airport pavement. First, based on the `inertial point' theory, the response modulus of the subgrade and the elastic modulus of concrete slab are calculated by using data from the field testing on the airport pavement. Then, stress and deflection of the pavement slab are analyzed using Winkler foundation model and finite element method. Finally, the PCN and the strength grade of airport pavement are determined. Results show that, through this procedure, PCN can be obtained efficiently. This study is helpful for the health and safe operation of airport pavement.

A new method of real-time GPS/WAAS user positioning quality control for transportation applications is considered. Current quality of positioning is defined through the GPS/WAAS user's required navigation parameters (RNP) such as positioning accuracy and positioning availability taking in account the current Positioning Delusion of Precision (PDOP). The method is based on real-time assessment of the RNP achievement total probability for the concrete GPS/WAAS user within WAAS coverage zone. The method allows detecting sudden positioning quality deterioration for the concrete RNP of aviation users and can be effectively used for some transportation applications which have strong RNP. Especially, the method can be recommended for transportation applications such as aviation landing systems and automatic railroad traffic control.

The dissipative structure theory suggests that whether an ordered system in the development process of evolution moves towards more advanced and ordered development or disordered development is determined by the random factors near the bifurcation point. In this article, this will be applied to civil aviation transportation system emergencies. First, it is pointed out that the civil aviation transportation system is a dissipative structure. Second, the dissipative structure theory is used to analyze the emergencies formation mechanism of the civil aviation transportation system. Finally, an effective civil aviation regulator is built to reduce the internal entropy increase, and the civil aviation incident management mechanism is established to control the random fluctuations to prevent and reduce the adverse impact of civil aviation crises. With the development of the national economy, the civil aviation transportation industry in China developed rapidly. Since 2005, the total turnover volume of civil aviation transportation has ranked second in the world. This remarkable achievement indicates that China has become the major power of the world's civil aviation, but the continuous expansion of transportation and passenger volume greatly increases the probability of emergencies and brings many problems and challenges to the civil aviation. As a high-risk industry, civil aviation should improve management, prevent the accidents, and enhance the emergency response capability in order to push forward the progress of the whole civil aviation industry in China. The dissipative structure theory in thermodynamics suggests that, in the process of evolution, whether an ordered system moves towards more advanced and ordered development or disordered is determined by the random factors nearby the bifurcation point. The system referred to in this theory can also be applied to the civil aviation transportation system. In this article, the formation reasons of the civil aviation transportation system emergencies will be studied under the perspective of the dissipative structure theory, and the corresponding pre-control management measures will be brought out.

The goal of this paper is to present the design process for air traffic Collaborative Decision-Making (CDM) based on multi-agent system. Currently, air traffic congestion and delays are the most severe problems facing the aviation industry, which causes inefficiency and traveler disappointment. To cope with the situation, CDM can be implemented to improve planning, on-time performance and operations in adverse conditions. During CDM implementation process, airport, ATC and airlines can discuss methods to solve problems in common interest; while in dynamic operation environment, all the actors of the air transport, which can be viewed as an agent individually, will need to negotiate to reach an optimal goal. The paper first introduces the roles and activities of airport, ATC (mainly terminal control, which deals with traffic inbound or outbound from a major or several major airports) and airline. Then, the article presents the negotiation process using Monotonic Concession Protocol among some actors. Finally, the paper provides a case to show the effectiveness of the CDM process using multi-agent system.

To the characteristics of air traffic management system, the safety risk coupling elements are analyzed on human factors, equipment factors, environment factors and management factors. The contribution of air traffic safety risk coupling elements is analyzed. The contribution of coupling elements are assessed by extension analytic hierarchy process (EAHP), taking inner communication risks, for instance, and the feasibility of the method is demonstrated by examination. The research objective is to determine the primary coupling element of the air traffic safety risk, propose the targeted pre-control program, so as to improve effectiveness of air traffic safety risk management.

Information Technology Infrastructure Library (ITIL) is a set of best practice guidelines for IT service management generally used in the industry. It is best practices summed up from the management experience of a large number of enterprise IT operation and maintenance services. In this paper, based on the analysis of network characteristics and prediction of development trends on the ITIL theory of service management mode, a new IT service management system is built for network. The proposed management system lines with the characteristics of network, provides safety process system, and is suitable to the industry's development direction. In addition, the system construction status is introduced, which is under the guidance of ITIL concepts. The future direction of the IT service management system construction is analyzed.

From the passenger-oriented aspect, this paper proposes an interactive evaluation methodology of transferring terminal design. This methodology applies passengers' satisfaction degree as evaluating measurements and is based on interactive simulation experiments. The objective evaluation about operation performances is also taken into consideration. In addition, this paper also applies HF1 engine to develop an ergonomic simulation platform helping evaluate the performance of passenger terminals. By this method, it helps to involve more public participation in inter-terminal sign designs before construction.

Air Traffic Control plays an important role in the safety of air transportation. Subsequently, the job stress of air traffic controllers is one of the factors that affect aviation safety. This paper uses SPSS11.5 and Amosl7.0 software to analyze the relationship between job stress and human errors through questionnaire data. The study shows that there is a significant positive correlation between job stress and human errors. The sources job stress for air traffic controllers include the stress of the job itself, role stress, interpersonal relation stress, organization structure and atmosphere stress, home/work conflict stress, and career development stress. The demographic variables that have an influence on human errors for air traffic controllers have also been confirmed, such as age, work experience, and level of education.

Most aviation accidents were due to human error. This paper focuses on the statistical analysis of aviation maintenance human error data, combining ergonomics and civil aviation maintenance theory to build the maintenance human error influence and prevention model, and on the maintenance human error causes from the man-machine-environment aspect, especially focusing on the three interfaces of man-man, man-machine (aircraft), and man-environment. Then, the human error prevention model was established based on the SHEL ergonomics theory from L-L, L-H, L-S, L-E, as well as the organization and management system aspect. Meanwhile, human error prevention recommendations were given. The conclusions provide a reference for the maintenance human error analysis and management.

The urban traffic network of Jinzhou city was split by the Beijing-Shenyang railway. The urban traffic intersects the south and north railways at only four bridge openings, and traffic congestion subsequently occurs in these areas. Railway crossing traffic in the Jinzhou urban district is analyzed. In order to find the operating characteristics of the north-south traffic and the most crowed bridge opening during the peak hour, the traffic and geometric characteristics of the bridge openings are analyzed. The traffic volumes of the bridge openings are investigated and analyzed. In addition, the peak hour and peak hour traffic volumes are found. The saturation degree of the bridge openings is then calculated. The study provides basic traffic information for traffic guidance.

To make commodity effective plays its space function and achieve the optimal allocation of resources. It will analyze the commodity from the perspective of space added value and research the influence of the residents' income and the degree of scarcity to the commodity space added value. According to space sensitivity degree, we will classify the different kinds of goods and create the optimal space added value model so that goods reasonable space configuration have optimization function.

As a large investment in the construction of urban infrastructure facilities, urban rail transit not only has transit and economic benefits, but also has enormous social and environmental benefits. In order to have a sufficient comprehension about the benefits urban rail transit brings, increase its investment and accelerate its construction, this article takes the urban rail transit as the research object, and analyzes the influence factors on the urban rail transit in the aspects of traffic, economy, society and environment. It will also establish a comprehensive benefits evaluation system for urban rail transit. To avoid the subjectivity calculation in the progress of evaluation, a double-hierarchy evaluation model based on the discrete catastrophe - extenics method, is introduced so as to improve the accuracy of the evaluation result. In the end, the evaluation method is applied to the case of the comprehensive benefits evaluation for the urban rail transit and the other urban passenger travel modes in Wuhan City. The results prove that the researching method used in this paper has a favorable effect, as well as referenced significance and applicable value for the planning and decision of the urban rail transit construction and operation.

Combined with the state of domestic urban transport development, the internet of things technology (IOT) and transportation industry development trends were analyzed, analysis of the breakthrough focus to develop ITS under IOT; the future transport development pattern was proposed. Used information collection system for IOT, it has good interactive interface and improves the function modules, which can be deployed in different scenarios to realize automatic acquisition and terminal handling. On the basis of information collected analyzing the relation between Rail Traffic train plan and transfer plan, taking into comprehensive consideration Rail Traffic economy benefits and passenger service quality, this paper builds a mathematics model of passenger transfer plan and puts forward the optimized algorithm based on the block-encoded improved genetic algorithm. The proposed algorithm is able to work out passenger transfer plans rapidly and accurately, and provides references to passenger flow optimum alternatives.